Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled...Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.展开更多
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ...The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.展开更多
Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.I...Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.展开更多
Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration...Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.展开更多
We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanorib...We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanoribbon and form the edge-to-edge antiferromagnetism. Under an in-plane electric field, the two degenerate edge bands of the edge-to-edge antiferromagnet split into four spin-polarized sub-bands and a 100% spin-polarized current can be easily induced with the maximal conductance 2e~2/h. The spin polarization changes with the strength of the electric field and the exchange field,and changes sign at opposite electric fields. The spin-polarized current switches from one edge to the other by reversing the direction of the electric field. The edge current can also be controlled spatially by changing the electric potential of the scattering region. The manipulation of edge current is useful in spin-transfer-torque magnetic random-access memory and provides a practical way to develop controllable spintronic devices.展开更多
To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior in...To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.展开更多
A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filte...A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.展开更多
Compact fifth-generation(5G)low-frequency band filtering antennas(filtennas)with stable directive radiation patterns,improved bandwidth(BW),and gain are designed,fabricated,and tested in this research.The proposed fil...Compact fifth-generation(5G)low-frequency band filtering antennas(filtennas)with stable directive radiation patterns,improved bandwidth(BW),and gain are designed,fabricated,and tested in this research.The proposed filtennas are achieved by combining the predesigned compact 5G(5.975–7.125 GHz)third-order uniform and non-uniform transmission line hairpin bandpass filters(UTL and NTL HPBFs)with the compact ultrawide band Vivaldi tapered slot antenna(UWB VTSA)in one module.The objective of this integration is to enhance the performance of 5.975–7.125GHz filtennas which will be suitable for modern mobile communication applications by exploiting the benefits of UWB VTSA.Based on NTL HPBF,more space is provided to add the direct current(DC)biassing circuits in cognitive radio networks(CRNs)for frequency reconfigurable applications.To overcome the mismatch between HPBFs and VTSA,detailed parametric studies are presented.Computer simulation technology(CST)software is used for the simulation in this study.Good measured S11 appeared to be<−13 and<−10.54 dB at 5.48–7.73 and 5.9–7.98GHz with peak realized gains of 6.37 and 6.27 dBi,for VTSA with UTL and NTL HPBFs,respectively which outperforms the predesigned filters.Validation is carried out by comparing the measured and simulated results.展开更多
BACKGROUND Overhanging filtering bleb is a common complication after trabeculectomy and surgical repair is an effective treatment when the patient presents with apparent symptoms.Filtering bleb relevant infection incl...BACKGROUND Overhanging filtering bleb is a common complication after trabeculectomy and surgical repair is an effective treatment when the patient presents with apparent symptoms.Filtering bleb relevant infection including in the filtering bleb itself and even endophthalmitis in some severe cases has been reported.However,corneal fungal infection after filtering bleb repair is rarely reported.CASE SUMMARY A 57-year-old Chinese man who had sensations of redness and foreign body sensations in the left eye 3 wk after repair of overhanging filtering bleb.3 wk ago,due to sensations of a foreign body in the left eye for 3 years with worsening for 3 mo.The patient was diagnosed as overhanging filtering bleb and underwent a repair of overhanging filtering bleb.Postoperative,the filtering bleb formed well and the intraocular pressure is normal.But the patient gradually develop redness,pain and a grey infiltrate of the cornea in the eye.Finally it developed into fungal corneal ulcer.Through asking the medical history,we found the patient had irregularly self-medicated for years with glucocorticoid eye drops for years to relieve the foreign body sensation in the eye caused by filtering bleb overhanging.Because the glucocorticoid eye drops he used years ago had provide normal sensation to the eye.After 3 mo of anti-fungal treatment,the inflammation was controlled.CONCLUSION In addition to avoiding the development of overhanging filtering bleb after trabeculectomy,the present case report also suggests that clinicians should pay more attention to the patient’s ocular self-medication history.Particularly in patients with a history of glaucoma or eye surgery.Because these patients may be exposed to more types of eye drops than other individuals,they may select the wrong medi-cations for long-term use,based on their previous experience.展开更多
In terms of the electromagnetic wave measurement while drilling,the extremely low frequency electromagnetic(ELF-EM)signal below 20Hz is usually chosen as the downhole data carrier.To improve the transmission rate of E...In terms of the electromagnetic wave measurement while drilling,the extremely low frequency electromagnetic(ELF-EM)signal below 20Hz is usually chosen as the downhole data carrier.To improve the transmission rate of ELF-EM signal and the signal to noise ratio(SNR)at the receiving end,the DQPSK modulation was proposed as the modulation method for the communication of electromagnetic wave system.Different from the traditional IQ orthogonal modulation and coherent demodulation methods,the proposed phase selection modulation and correlation algorithm demodulation are easier to implement and more practical.With regard to the communication synchronization,a fast algorithm,which based on the normalized cross-relation number,was used for waveform matching,and the maximum point of the correlation coefficient was used as the starting point of communication synchronization.The communication simulation results show that the proposed DQPSK modulation signal based on the adaptive combined filtering algorithm has better terminal error rate and transmission rate than the traditional modulation method.Under the same carrier frequency and code width,the transmission rate of DQPSK modulation is 4 to 5 times and 2 times that of PPM modulation and 2DPSK modulation respectively.The communication modulation and demodulation modes as well as the decoding algorithm with combined adaptive filter proposed in this paper can effectively solve practical engineering problems.展开更多
Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep lear...Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services.展开更多
Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring...Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring.A commonly practiced approach of filtering with nonlinear systems is Gaussian filtering.The early Gaussian filters used a derivative-based implementation,and suffered from several drawbacks,such as the smoothness requirements of system models and poor stability.A derivative-free numerical approximation-based Gaussian filter,named the unscented Kalman filter(UKF),was introduced in the nineties,which offered several advantages over the derivativebased Gaussian filters.Since the proposition of UKF,derivativefree Gaussian filtering has been a highly active research area.This paper reviews significant developments made under Gaussian filtering since the proposition of UKF.The review is particularly focused on three categories of developments:i)advancing the numerical approximation methods;ii)modifying the conventional Gaussian approach to further improve the filtering performance;and iii)constrained filtering to address the problem of discrete-time formulation of process dynamics.This review highlights the computational aspect of recent developments in all three categories.The performance of various filters are analyzed by simulating them with real-life target tracking problems.展开更多
Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspe...Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.展开更多
Elucidating how multiple factors affect biodiversity and plant community assembly is a central issue in ecology,especially in vulnerable ecosystems such as tropical mountains.These studies are more relevant in global ...Elucidating how multiple factors affect biodiversity and plant community assembly is a central issue in ecology,especially in vulnerable ecosystems such as tropical mountains.These studies are more relevant in global warming scenarios that induce the upward displacement of plant species towards reduced habitats and hostile environments in tropical mountains.This study aimed to analyze how altitude affects taxonomic and phylogenetic diversity in plant communities of tropical mountains.Thus,we tested if(i)increased altitude works as an environmental filtering promoting decreased species richness,decreased phylogenetic diversity,and increased phylogenetic clustering in these tropical mountains;and if(ii)plant communities of high altitude in tropical mountains are also result of recent diversification with plant species recently split shortening phylogenetic distances between closest related species.We tested effects of altitude on species richness and phylogenetic metrics using linear mixed-effects models.Mount Haleakala presented 114 species,Mount Kilimanjaro presented 231 species and Mount Purace presented 280 species.We found an environmental filtering effect with increasing altitude causing phylogenetic clustering,decreased phylogenetic diversity and decreased species richness.The decreasing phylogenetic distances between closest relatives are congruent with neo-endemics,suggesting recent plant diversification in high altitudes of tropical mountains,possibly driven by geographic isolation and environmental heterogeneity.Consequences of global warming should be monitored in tropical mountains focusing on distribution shifts.展开更多
In this article,a single-layer symmetrical full-port quasi-absorptive filtering phase shifter is presented.The proposed phase shifter is composed of a main quasi-absorptive filtering branch,a reference quasi-absorptiv...In this article,a single-layer symmetrical full-port quasi-absorptive filtering phase shifter is presented.The proposed phase shifter is composed of a main quasi-absorptive filtering branch,a reference quasi-absorptive filtering branch,and two delay lines.The proposed phase shifter achieves both phase controlling function and quasi-absorptive filtering function for the first time.Each quasi-absorptive filtering branch can realize the quasi-absorptive filtering function.Meanwhile,the constant phase shift can be obtained by combining the two quasi-absorptive filtering branches and the two delay lines.The design formulas can be derived from the even-and odd-mode network analysis,and then two quasi-absorptive filtering phase shifters can be devised easily and quickly.For verification,a 90°quasi-absorptive filtering phase shifter,which is critical for circularly polarized antenna systems,is simulated,manufactured,and measured.展开更多
Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landsl...Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landslide deformation.Based on the study of landslide block,this paper regarded the landslide block as a rigid body in particle swarm optimization algorithm.The monitoring data were organized to achieve the optimal state of landslide block,and the 6-degree of freedom pose of the landslide block was calculated after the regularization.Based on the characteristics of data from multiple monitoring points of landslide blocks,a prediction equation for the motion state of landslide blocks was established.By using Kalman filtering data assimilation method,the parameters of prediction equation for landslide block motion state were adjusted to achieve the optimal prediction.This paper took the Baishuihe landslide in the Three Gorges reservoir area as the research object.Based on the block segmentation of the landslide,the monitoring data of the Baishuihe landslide block were organized,6-degree of freedom pose of block B was calculated,and the Kalman filtering data assimilation method was used to predict the landslide block movement.The research results showed that the proposed prediction method of the landslide movement state has good prediction accuracy and meets the expected goal.This paper provides a new research method and thinking angle to study the motion state of landslide block.展开更多
In this paper,a 5G wideband power amplifier(PA)with bandpass filtering response is synthesized using a bandwidth-extended bandpass filter as the matching network(MN).In this structure,the bandwidth(θ_(C))is defined a...In this paper,a 5G wideband power amplifier(PA)with bandpass filtering response is synthesized using a bandwidth-extended bandpass filter as the matching network(MN).In this structure,the bandwidth(θ_(C))is defined as a variable in the closedform equations provided by the microstrip bandpass filter.It can be extended over a wide range only by changing the characteristic impedances of the structure.Different from the other wideband MNs,the extension of bandwidth does not increase the complexity of the structure(order n is fixed).In addition,based on the bandwidth-extended structure,the wideband design of bandpass filtering PA is not limited to the fixed bandwidth of the specific filter structure.The theoretical analysis of the MN and the design flow of the PA are provided in this design.The fabricated bandpass filtering PA can support almost one-octave bandwidth(2-3.8 GHz),covering the two 5G bands(n41 and n78).The drain efficiency of 47%-60%and output power higher than 40 dBm are measured.Good frequency selectivity in S-parameter measurements can be observed.展开更多
Dear Editor,This letter concerns about the distributed dimensionally reduction filtering for a class of cyber physical systems with denial of service(DoS)attacks.Considering each sensor exchanging measurements with ne...Dear Editor,This letter concerns about the distributed dimensionally reduction filtering for a class of cyber physical systems with denial of service(DoS)attacks.Considering each sensor exchanging measurements with neighbors subjected to finite network energy,the dimensionally reduction method is applied.展开更多
In this paper,an integrated substrate gap waveguide(ISGW)filtering antenna is proposed at millimeter wave band,whose surface wave and spurious modes are simultaneously suppressed.A secondorder filtering response is ob...In this paper,an integrated substrate gap waveguide(ISGW)filtering antenna is proposed at millimeter wave band,whose surface wave and spurious modes are simultaneously suppressed.A secondorder filtering response is obtained through a coupling feeding scheme using one uniform impedance resonator(UIR)and two stepped-impedance resonators(SIRs).To increase the stopband width of the antenna,the spurious modes are suppressed by selecting the appropriate sizes of the ISGW unit cell.Furthermore,the ISGW is implemented to improve the radiation performance of the antenna by alleviating the propagation of surface wave.And an equivalent circuit is investigated to reveal the working principle of ISGW.To demonstrate this methodology,an ISGW filtering antenna operating at a center frequency of 25 GHz is designed,fabricated,and measured.The results show that the antenna achieves a stopband width of 1.6f0(center frequency),an out-of-band suppression level of 21 dB,and a peak realized gain of 8.5 dBi.展开更多
In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quali...In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.展开更多
文摘Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.
基金supported in part by the National Natural Science Foundation of China (62233012,62273087)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Shanghai Pujiang Program of China (22PJ1400400)。
文摘The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.
文摘Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.
基金supported by the National Natural Science Foundation of China (Nos.51975447,52275268)National Key Research and Development Program of China (No.2021YFC2203600)+2 种基金National Defense Basic Scientific Research Program of China (No.JCKY2021210B007)the Project about Building up“Scientists+Engineers”of Shaanxi Qinchuangyuan Platform (No.2022KXJ-030)Wuhu and Xidian University Special Fund for Industry University Research Cooperation (No.XWYCXY012021-012)。
文摘Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.12174077 and 12174051)the Science Foundation of GuangDong Province (Grant No.2021A1515012363)GuangDong Basic and Applied Basic Research Foundation (Grant No.2022A1515110011)。
文摘We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanoribbon and form the edge-to-edge antiferromagnetism. Under an in-plane electric field, the two degenerate edge bands of the edge-to-edge antiferromagnet split into four spin-polarized sub-bands and a 100% spin-polarized current can be easily induced with the maximal conductance 2e~2/h. The spin polarization changes with the strength of the electric field and the exchange field,and changes sign at opposite electric fields. The spin-polarized current switches from one edge to the other by reversing the direction of the electric field. The edge current can also be controlled spatially by changing the electric potential of the scattering region. The manipulation of edge current is useful in spin-transfer-torque magnetic random-access memory and provides a practical way to develop controllable spintronic devices.
基金the National Natural Science Fund of China(61471080)Training Plan for Young Backbone Teachers in Colleges and Universities of Henan Province(2018GGJS171).
文摘To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.
基金supported by National Natural Science Foundation of China (Nos.62265010,62061024)Gansu Province Science and Technology Plan (No.23YFGA0062)Gansu Province Innovation Fund (No.2022A-215)。
文摘A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.
基金This work was supported by the Postdoctoral Fellowship Scheme under the Professional Development Research University from Universiti Teknologi Malaysia(UTM)under Grant 06E07.
文摘Compact fifth-generation(5G)low-frequency band filtering antennas(filtennas)with stable directive radiation patterns,improved bandwidth(BW),and gain are designed,fabricated,and tested in this research.The proposed filtennas are achieved by combining the predesigned compact 5G(5.975–7.125 GHz)third-order uniform and non-uniform transmission line hairpin bandpass filters(UTL and NTL HPBFs)with the compact ultrawide band Vivaldi tapered slot antenna(UWB VTSA)in one module.The objective of this integration is to enhance the performance of 5.975–7.125GHz filtennas which will be suitable for modern mobile communication applications by exploiting the benefits of UWB VTSA.Based on NTL HPBF,more space is provided to add the direct current(DC)biassing circuits in cognitive radio networks(CRNs)for frequency reconfigurable applications.To overcome the mismatch between HPBFs and VTSA,detailed parametric studies are presented.Computer simulation technology(CST)software is used for the simulation in this study.Good measured S11 appeared to be<−13 and<−10.54 dB at 5.48–7.73 and 5.9–7.98GHz with peak realized gains of 6.37 and 6.27 dBi,for VTSA with UTL and NTL HPBFs,respectively which outperforms the predesigned filters.Validation is carried out by comparing the measured and simulated results.
基金Supported by the Science and Technology Project of Education Department of Jilin Province,No.JJKH20201089KJ.
文摘BACKGROUND Overhanging filtering bleb is a common complication after trabeculectomy and surgical repair is an effective treatment when the patient presents with apparent symptoms.Filtering bleb relevant infection including in the filtering bleb itself and even endophthalmitis in some severe cases has been reported.However,corneal fungal infection after filtering bleb repair is rarely reported.CASE SUMMARY A 57-year-old Chinese man who had sensations of redness and foreign body sensations in the left eye 3 wk after repair of overhanging filtering bleb.3 wk ago,due to sensations of a foreign body in the left eye for 3 years with worsening for 3 mo.The patient was diagnosed as overhanging filtering bleb and underwent a repair of overhanging filtering bleb.Postoperative,the filtering bleb formed well and the intraocular pressure is normal.But the patient gradually develop redness,pain and a grey infiltrate of the cornea in the eye.Finally it developed into fungal corneal ulcer.Through asking the medical history,we found the patient had irregularly self-medicated for years with glucocorticoid eye drops for years to relieve the foreign body sensation in the eye caused by filtering bleb overhanging.Because the glucocorticoid eye drops he used years ago had provide normal sensation to the eye.After 3 mo of anti-fungal treatment,the inflammation was controlled.CONCLUSION In addition to avoiding the development of overhanging filtering bleb after trabeculectomy,the present case report also suggests that clinicians should pay more attention to the patient’s ocular self-medication history.Particularly in patients with a history of glaucoma or eye surgery.Because these patients may be exposed to more types of eye drops than other individuals,they may select the wrong medi-cations for long-term use,based on their previous experience.
基金supported by National Natural Science Foundation of China(No.61771366)Stable-Support Scientific Project of China Research Institute of Radiowave Propagation(Grant No.A132201068 and No.A132107W08)。
文摘In terms of the electromagnetic wave measurement while drilling,the extremely low frequency electromagnetic(ELF-EM)signal below 20Hz is usually chosen as the downhole data carrier.To improve the transmission rate of ELF-EM signal and the signal to noise ratio(SNR)at the receiving end,the DQPSK modulation was proposed as the modulation method for the communication of electromagnetic wave system.Different from the traditional IQ orthogonal modulation and coherent demodulation methods,the proposed phase selection modulation and correlation algorithm demodulation are easier to implement and more practical.With regard to the communication synchronization,a fast algorithm,which based on the normalized cross-relation number,was used for waveform matching,and the maximum point of the correlation coefficient was used as the starting point of communication synchronization.The communication simulation results show that the proposed DQPSK modulation signal based on the adaptive combined filtering algorithm has better terminal error rate and transmission rate than the traditional modulation method.Under the same carrier frequency and code width,the transmission rate of DQPSK modulation is 4 to 5 times and 2 times that of PPM modulation and 2DPSK modulation respectively.The communication modulation and demodulation modes as well as the decoding algorithm with combined adaptive filter proposed in this paper can effectively solve practical engineering problems.
文摘Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services.
文摘Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring.A commonly practiced approach of filtering with nonlinear systems is Gaussian filtering.The early Gaussian filters used a derivative-based implementation,and suffered from several drawbacks,such as the smoothness requirements of system models and poor stability.A derivative-free numerical approximation-based Gaussian filter,named the unscented Kalman filter(UKF),was introduced in the nineties,which offered several advantages over the derivativebased Gaussian filters.Since the proposition of UKF,derivativefree Gaussian filtering has been a highly active research area.This paper reviews significant developments made under Gaussian filtering since the proposition of UKF.The review is particularly focused on three categories of developments:i)advancing the numerical approximation methods;ii)modifying the conventional Gaussian approach to further improve the filtering performance;and iii)constrained filtering to address the problem of discrete-time formulation of process dynamics.This review highlights the computational aspect of recent developments in all three categories.The performance of various filters are analyzed by simulating them with real-life target tracking problems.
文摘Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.
基金provided by FAPEMIG(FORTIS/PPGBot-UFV,PPM-00584-16,APQ‐01309‐16)CAPES(PROAP and PrInt/PPGBot-UFV),CNPq(307591/2016‐6,306335/2020-4).
文摘Elucidating how multiple factors affect biodiversity and plant community assembly is a central issue in ecology,especially in vulnerable ecosystems such as tropical mountains.These studies are more relevant in global warming scenarios that induce the upward displacement of plant species towards reduced habitats and hostile environments in tropical mountains.This study aimed to analyze how altitude affects taxonomic and phylogenetic diversity in plant communities of tropical mountains.Thus,we tested if(i)increased altitude works as an environmental filtering promoting decreased species richness,decreased phylogenetic diversity,and increased phylogenetic clustering in these tropical mountains;and if(ii)plant communities of high altitude in tropical mountains are also result of recent diversification with plant species recently split shortening phylogenetic distances between closest related species.We tested effects of altitude on species richness and phylogenetic metrics using linear mixed-effects models.Mount Haleakala presented 114 species,Mount Kilimanjaro presented 231 species and Mount Purace presented 280 species.We found an environmental filtering effect with increasing altitude causing phylogenetic clustering,decreased phylogenetic diversity and decreased species richness.The decreasing phylogenetic distances between closest relatives are congruent with neo-endemics,suggesting recent plant diversification in high altitudes of tropical mountains,possibly driven by geographic isolation and environmental heterogeneity.Consequences of global warming should be monitored in tropical mountains focusing on distribution shifts.
基金supported by National Natural Science Foundations of China(No.U20A20203,No.61971052,U21A20510)the Fundamental Research Funds for the Central Universities(2021XDA07-1)Key Research and Development Project of Guangdong Province(2020B0101080001)。
文摘In this article,a single-layer symmetrical full-port quasi-absorptive filtering phase shifter is presented.The proposed phase shifter is composed of a main quasi-absorptive filtering branch,a reference quasi-absorptive filtering branch,and two delay lines.The proposed phase shifter achieves both phase controlling function and quasi-absorptive filtering function for the first time.Each quasi-absorptive filtering branch can realize the quasi-absorptive filtering function.Meanwhile,the constant phase shift can be obtained by combining the two quasi-absorptive filtering branches and the two delay lines.The design formulas can be derived from the even-and odd-mode network analysis,and then two quasi-absorptive filtering phase shifters can be devised easily and quickly.For verification,a 90°quasi-absorptive filtering phase shifter,which is critical for circularly polarized antenna systems,is simulated,manufactured,and measured.
基金supported by National Natural Science Foundation of China(Grant Nos.42090054,52027814 and 41772376)the Open Fund of the Technology Innovation Center for Automated Geological Disaster Monitoring,Ministry of Natural Resources(Grant No.2022058014)。
文摘Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landslide deformation.Based on the study of landslide block,this paper regarded the landslide block as a rigid body in particle swarm optimization algorithm.The monitoring data were organized to achieve the optimal state of landslide block,and the 6-degree of freedom pose of the landslide block was calculated after the regularization.Based on the characteristics of data from multiple monitoring points of landslide blocks,a prediction equation for the motion state of landslide blocks was established.By using Kalman filtering data assimilation method,the parameters of prediction equation for landslide block motion state were adjusted to achieve the optimal prediction.This paper took the Baishuihe landslide in the Three Gorges reservoir area as the research object.Based on the block segmentation of the landslide,the monitoring data of the Baishuihe landslide block were organized,6-degree of freedom pose of block B was calculated,and the Kalman filtering data assimilation method was used to predict the landslide block movement.The research results showed that the proposed prediction method of the landslide movement state has good prediction accuracy and meets the expected goal.This paper provides a new research method and thinking angle to study the motion state of landslide block.
基金supported by National Natural Science Foundations of China (No.61971052 and No.U20A20203)Key Research and Development Project of Guangdong Province (2020B0101080001)
文摘In this paper,a 5G wideband power amplifier(PA)with bandpass filtering response is synthesized using a bandwidth-extended bandpass filter as the matching network(MN).In this structure,the bandwidth(θ_(C))is defined as a variable in the closedform equations provided by the microstrip bandpass filter.It can be extended over a wide range only by changing the characteristic impedances of the structure.Different from the other wideband MNs,the extension of bandwidth does not increase the complexity of the structure(order n is fixed).In addition,based on the bandwidth-extended structure,the wideband design of bandpass filtering PA is not limited to the fixed bandwidth of the specific filter structure.The theoretical analysis of the MN and the design flow of the PA are provided in this design.The fabricated bandpass filtering PA can support almost one-octave bandwidth(2-3.8 GHz),covering the two 5G bands(n41 and n78).The drain efficiency of 47%-60%and output power higher than 40 dBm are measured.Good frequency selectivity in S-parameter measurements can be observed.
基金This work was supported by the National Natural Science Foundation of China(62103130,62273255)the Shanghai International Science and Technology Cooperation Project(22510712000)the Fundamental Research Funds for the Central Universities.
文摘Dear Editor,This letter concerns about the distributed dimensionally reduction filtering for a class of cyber physical systems with denial of service(DoS)attacks.Considering each sensor exchanging measurements with neighbors subjected to finite network energy,the dimensionally reduction method is applied.
基金This work was supported by the National Key research and development program of China(No.2021YFB 2900401)the national natural science foundation of China(No.62361057,No.61861046)+1 种基金the key natural science foundation of Shenzhen(No.JCYJ20220818102209020)the key research and development program of Shenzhen(No.ZDSYS20210623091807023).
文摘In this paper,an integrated substrate gap waveguide(ISGW)filtering antenna is proposed at millimeter wave band,whose surface wave and spurious modes are simultaneously suppressed.A secondorder filtering response is obtained through a coupling feeding scheme using one uniform impedance resonator(UIR)and two stepped-impedance resonators(SIRs).To increase the stopband width of the antenna,the spurious modes are suppressed by selecting the appropriate sizes of the ISGW unit cell.Furthermore,the ISGW is implemented to improve the radiation performance of the antenna by alleviating the propagation of surface wave.And an equivalent circuit is investigated to reveal the working principle of ISGW.To demonstrate this methodology,an ISGW filtering antenna operating at a center frequency of 25 GHz is designed,fabricated,and measured.The results show that the antenna achieves a stopband width of 1.6f0(center frequency),an out-of-band suppression level of 21 dB,and a peak realized gain of 8.5 dBi.
基金supported in part by the National Natural Science Foundation of China(Nos.62201051,62101039)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by the National Key Research and Development Program of China(No.SQ2022YFB3900055).
文摘In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.
