This paper presents a comprehensive framework for analyzing phase transitions in collective models such as theVicsek model under various noise types. The Vicsek model, focusing on understanding the collective behavior...This paper presents a comprehensive framework for analyzing phase transitions in collective models such as theVicsek model under various noise types. The Vicsek model, focusing on understanding the collective behaviors of socialanimals, is known due to its discontinuous phase transitions under vector noise. However, its behavior under scalar noiseremains less conclusive. Renowned for its efficacy in the analysis of complex systems under both equilibrium and nonequilibriumstates, the eigen microstate method is employed here for a quantitative examination of the phase transitions inthe Vicsek model under both vector and scalar noises. The study finds that the Vicsek model exhibits discontinuous phasetransitions regardless of noise type. Furthermore, the dichotomy method is utilized to identify the critical points for thesephase transitions. A significant finding is the observed increase in the critical point for discontinuous phase transitions withescalation of population density.展开更多
In the processing of conventional marine seismic data,seawater is often assumed to have a constant velocity model.However,due to static pressure,temperature difference and other factors,random disturbances may often f...In the processing of conventional marine seismic data,seawater is often assumed to have a constant velocity model.However,due to static pressure,temperature difference and other factors,random disturbances may often frequently in seawater bodies.The impact of such disturbances on data processing results is a topic of theoretical research.Since seawater sound velocity is a difficult physical quantity to measure,there is a need for a method that can generate models conforming to seawater characteristics.This article will combine the Munk model and Perlin noise to propose a two-dimensional dynamic seawater sound velocity model generation method,a method that can generate a dynamic,continuous,random seawater sound velocity model with some regularity at large scales.Moreover,the paper discusses the influence of the inhomogeneity characteristics of seawater on wave field propagation and imaging.The results show that the seawater sound velocity model with random disturbance will have a significant influence on the wave field simulation and imaging results.展开更多
This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a suffi...This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.展开更多
A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate...A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.展开更多
The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode n...The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode noise of the converter.Traditionally,the measurement method is used for transformer modeling,and a single lumped device is used to establish the transformer model,which cannot be predicted in the transformer design stage.Based on the transformer common-mode noise transmission mechanism,this paper derives the transformer common-mode equivalent capacitance under ideal conditions.According to the principle of experimental measurement of the network analyzer,the electromagnetic field finite element simulation software three-dimensional(3D)modeling and simulation method is used to obtain the two-port parameters of the transformer,extract the high-frequency parameters of the transformer,and establish its electromagnetic compatibility equivalent circuit model.Finally,an experimental prototype is used to verify the correctness of the model by comparing the experimental measurement results with the simulation prediction results.展开更多
The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random t...The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.展开更多
Due to the limitations of a priori knowledge and convolution operation,the existing image restoration techniques cannot be directly applied to the cultural relics mural restoration,in order to more accurately restore ...Due to the limitations of a priori knowledge and convolution operation,the existing image restoration techniques cannot be directly applied to the cultural relics mural restoration,in order to more accurately restore the original appearance of the cultural relics mural images,an image restoration based on the denoising diffusion probability model(Denoising Diffusion Probability Model(DDPM))and the Transformer method.The process involves two steps:in the first step,the damaged mural image is firstly utilized as the condition to generate the noise image,using the time,condition and noise image patch as the inputs to the noise prediction network,capturing the global dependencies in the input sequence through the multi-attentionmechanismof the input sequence and feedforward neural network processing,and designing a long skip connection between the shallow and deep layers in the Transformer blocks between the shallow and deep layers using long skip connections to fuse the feature information of global and local outputs to maintain the overall consistency of the restoration results;In the second step,taking the noisy image as a condition to direct the diffusion model to back sample to generate the restored image.Experiment results show that the PSNR and SSIM of the proposedmethod are improved by 2%to 9%and 1%to 3.3%,respectively,which are compared to the comparison methods.This study proposed synthesizes the advantages of the diffusionmodel and deep learningmodel to make themural restoration results more accurate.展开更多
Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control l...Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.展开更多
In view of the limitations of a Rn-Gn model in the low frequency range and the defects of an En-In model in common use now, this paper builds a complete En-In model according to the theory of random harmonic. The para...In view of the limitations of a Rn-Gn model in the low frequency range and the defects of an En-In model in common use now, this paper builds a complete En-In model according to the theory of random harmonic. The parameters for the low-noise design such as the equivalent input noisy voltage Ens, the optimum source impedance Zsopt and the minimum noise figure Fmin can be calculated accurately by using this En-In model because it considers the coherence between the noise sources fully. Moreover, this paper points out that it will cause the maximum 30% miscalculation when neglecting the effects of the correlation coefficient 7. Using the series-series circuits as an example, this paper discusses the methods for the En-In noise analysis of electronic circuits preliminarily and demonstrates its correctness through the comparison between the simulated and measured results of the minimum noise figure Fmin of a single current series negative feedback circuit.展开更多
Based on the active coupled line concept, a novel approach for efficient signal and noise modeling of millimeter-wave field-effect transistors is proposed. The distributed model considers the effect of wave propagatio...Based on the active coupled line concept, a novel approach for efficient signal and noise modeling of millimeter-wave field-effect transistors is proposed. The distributed model considers the effect of wave propagation along the device electrodes, which can significantly affect the device performance especially in the millimetre-wave range. By solving the multi-conductor transmission line equations using the Finite-Difference Time-Domain technique, the proposed procedure can accurately determine the signal and noise performance of the transistor. In order to demonstrate the proposed FET model accuracy, a distributed low-noise amplifier was designed and tested. A model selection is often a trade-off between procedure complexity and response accuracy. Using the proposed distributed model versus the circuit-based model will allow increasing the model frequency range.展开更多
全球导航卫星系统GNSS对流层天顶湿延迟(zenith wet delay,ZWD)随机噪声不仅影响ZWD估计值大小,还会影响ZWD的趋势项变化。为揭示ZWD随机游走过程噪声(random walk process noise,RWPN)的时空变化特征,本文选取全球20个IGS(Internationa...全球导航卫星系统GNSS对流层天顶湿延迟(zenith wet delay,ZWD)随机噪声不仅影响ZWD估计值大小,还会影响ZWD的趋势项变化。为揭示ZWD随机游走过程噪声(random walk process noise,RWPN)的时空变化特征,本文选取全球20个IGS(International GNSS Service)测站,基于JPL(Jet Propulsion Laboratory)、GFZ(Helmholtz-Centre Potsdam-German Research Centre for Geosciences)和CODE(Center for Orbit Determination in Europe)分析中心2010至2020年对流层产品,从不同地理位置和不同时间序列分析GNSS ZWD随机游走过程噪声的变化范围和特征;并且在扣除ZWD的趋势项和主要周期项后,进一步揭示了ZWD残差信号分量构成。结果表明:不同地理位置湿延迟RWPN具有显著差异,年均值范围在0.01~0.146 mm/√s之间,且在大气集中的中低纬地区湿延迟RWPN值较大,在大气相对稀薄的极地地区其值较小;同一测站的湿延迟RWPN具有明显的周年、半周年和季节性特征,极差值高达0.12 mm/√s以上;通过对ZWD残差值分析,发现ZWD残差信号除包含白噪声外,还具有4.8 h至2.43 d的高频信号分量。展开更多
A new approach to conductive electromagnetic interference （EMI） noise source modeling, i. e. the source internal impedance extraction, is presented. First, the impedance magnitude is achieved through an exciting pro...A new approach to conductive electromagnetic interference （EMI） noise source modeling, i. e. the source internal impedance extraction, is presented. First, the impedance magnitude is achieved through an exciting probe and a detecting probe, or through calculations based on insertion loss measurement results when inserting a series nigh-value known impedance or a shunt low-value known impedance in the circuit. Then the impedance phase is extracted by the Hilbert transform （HT） of the logarithm of the obtained impedance magnitude. Performance studies show that the estimated phase error can increase greatly at a zero frequency in the Hilbert transform because of the existence of a singular point, and this effect can be eliminated by introducing a zero-point when the noise source does not include a series-connected capacitive component. It is also found that when the frequency is nigher than 150 kHz, the estimated phase error is not sensitive to the inductive source but sensitive to the capacitive source. Finally, under the conditions of the same measurement accuracies for impedance magnitude, the accuracy of complex impedance based on the HT can be improved about 10 times when compared with the accuracy of estimated parameters based on the impedance magnitude fitting method （IMFM）.展开更多
The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expres...The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expression of the exit probability is obtained using the Taylor expansion and the infinitesimal generator theory. Based on numerical calculations, it is found that the immune delay facilitates tumor extinction when the stability index α〈 1, but inhibits tumor extinction when the stability index α 〉 1. Moreover, larger stability index and smaller noise intensity are in favor of the extinction for tumor with low density. While for tumor with high density, the stability index and the noise intensity should be reduced to promote tumor extinction.展开更多
基金the National Natural Science Foundation of China(Grant No.62273033).
文摘This paper presents a comprehensive framework for analyzing phase transitions in collective models such as theVicsek model under various noise types. The Vicsek model, focusing on understanding the collective behaviors of socialanimals, is known due to its discontinuous phase transitions under vector noise. However, its behavior under scalar noiseremains less conclusive. Renowned for its efficacy in the analysis of complex systems under both equilibrium and nonequilibriumstates, the eigen microstate method is employed here for a quantitative examination of the phase transitions inthe Vicsek model under both vector and scalar noises. The study finds that the Vicsek model exhibits discontinuous phasetransitions regardless of noise type. Furthermore, the dichotomy method is utilized to identify the critical points for thesephase transitions. A significant finding is the observed increase in the critical point for discontinuous phase transitions withescalation of population density.
基金The General Program of National Natural Science Foundation of China under contract No.42074150。
文摘In the processing of conventional marine seismic data,seawater is often assumed to have a constant velocity model.However,due to static pressure,temperature difference and other factors,random disturbances may often frequently in seawater bodies.The impact of such disturbances on data processing results is a topic of theoretical research.Since seawater sound velocity is a difficult physical quantity to measure,there is a need for a method that can generate models conforming to seawater characteristics.This article will combine the Munk model and Perlin noise to propose a two-dimensional dynamic seawater sound velocity model generation method,a method that can generate a dynamic,continuous,random seawater sound velocity model with some regularity at large scales.Moreover,the paper discusses the influence of the inhomogeneity characteristics of seawater on wave field propagation and imaging.The results show that the seawater sound velocity model with random disturbance will have a significant influence on the wave field simulation and imaging results.
基金supported by the National Natural Science Foundation of China under Grants 61821004,62250056,62350710214,U23A20325,62350055the Natural Science Foundation of Shandong Province,China(ZR2021ZD14,ZR2021JQ24)+2 种基金High-level Talent Team Project of Qingdao West Coast New Area,China(RCTD-JC-2019-05)Key Research and Development Program of Shandong Province,China(2020CXGC01208)Science and Technology Project of Qingdao West Coast New Area,China(2019-32,2020-20,2020-1-4).
文摘This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.
文摘A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.
文摘The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode noise of the converter.Traditionally,the measurement method is used for transformer modeling,and a single lumped device is used to establish the transformer model,which cannot be predicted in the transformer design stage.Based on the transformer common-mode noise transmission mechanism,this paper derives the transformer common-mode equivalent capacitance under ideal conditions.According to the principle of experimental measurement of the network analyzer,the electromagnetic field finite element simulation software three-dimensional(3D)modeling and simulation method is used to obtain the two-port parameters of the transformer,extract the high-frequency parameters of the transformer,and establish its electromagnetic compatibility equivalent circuit model.Finally,an experimental prototype is used to verify the correctness of the model by comparing the experimental measurement results with the simulation prediction results.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61372156 and 61405053)the Natural Science Foundation of Zhejiang Province of China(Grant No.LZ13F04001)
文摘The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.
基金financial support from Hunan Provincial Natural Science and Technology Fund Project(Grant No.2022JJ50077)Natural Science Foundation of Hunan Province(Grant No.2024JJ8055).
文摘Due to the limitations of a priori knowledge and convolution operation,the existing image restoration techniques cannot be directly applied to the cultural relics mural restoration,in order to more accurately restore the original appearance of the cultural relics mural images,an image restoration based on the denoising diffusion probability model(Denoising Diffusion Probability Model(DDPM))and the Transformer method.The process involves two steps:in the first step,the damaged mural image is firstly utilized as the condition to generate the noise image,using the time,condition and noise image patch as the inputs to the noise prediction network,capturing the global dependencies in the input sequence through the multi-attentionmechanismof the input sequence and feedforward neural network processing,and designing a long skip connection between the shallow and deep layers in the Transformer blocks between the shallow and deep layers using long skip connections to fuse the feature information of global and local outputs to maintain the overall consistency of the restoration results;In the second step,taking the noisy image as a condition to direct the diffusion model to back sample to generate the restored image.Experiment results show that the PSNR and SSIM of the proposedmethod are improved by 2%to 9%and 1%to 3.3%,respectively,which are compared to the comparison methods.This study proposed synthesizes the advantages of the diffusionmodel and deep learningmodel to make themural restoration results more accurate.
基金funding by Comunidad de Madrid within the framework of the Multiannual Agreement with Universidad Politécnica de Madrid to encourage research by young doctors(PRINCE project).
文摘Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.
文摘In view of the limitations of a Rn-Gn model in the low frequency range and the defects of an En-In model in common use now, this paper builds a complete En-In model according to the theory of random harmonic. The parameters for the low-noise design such as the equivalent input noisy voltage Ens, the optimum source impedance Zsopt and the minimum noise figure Fmin can be calculated accurately by using this En-In model because it considers the coherence between the noise sources fully. Moreover, this paper points out that it will cause the maximum 30% miscalculation when neglecting the effects of the correlation coefficient 7. Using the series-series circuits as an example, this paper discusses the methods for the En-In noise analysis of electronic circuits preliminarily and demonstrates its correctness through the comparison between the simulated and measured results of the minimum noise figure Fmin of a single current series negative feedback circuit.
文摘Based on the active coupled line concept, a novel approach for efficient signal and noise modeling of millimeter-wave field-effect transistors is proposed. The distributed model considers the effect of wave propagation along the device electrodes, which can significantly affect the device performance especially in the millimetre-wave range. By solving the multi-conductor transmission line equations using the Finite-Difference Time-Domain technique, the proposed procedure can accurately determine the signal and noise performance of the transistor. In order to demonstrate the proposed FET model accuracy, a distributed low-noise amplifier was designed and tested. A model selection is often a trade-off between procedure complexity and response accuracy. Using the proposed distributed model versus the circuit-based model will allow increasing the model frequency range.
文摘全球导航卫星系统GNSS对流层天顶湿延迟(zenith wet delay,ZWD)随机噪声不仅影响ZWD估计值大小,还会影响ZWD的趋势项变化。为揭示ZWD随机游走过程噪声(random walk process noise,RWPN)的时空变化特征,本文选取全球20个IGS(International GNSS Service)测站,基于JPL(Jet Propulsion Laboratory)、GFZ(Helmholtz-Centre Potsdam-German Research Centre for Geosciences)和CODE(Center for Orbit Determination in Europe)分析中心2010至2020年对流层产品,从不同地理位置和不同时间序列分析GNSS ZWD随机游走过程噪声的变化范围和特征;并且在扣除ZWD的趋势项和主要周期项后,进一步揭示了ZWD残差信号分量构成。结果表明:不同地理位置湿延迟RWPN具有显著差异,年均值范围在0.01~0.146 mm/√s之间,且在大气集中的中低纬地区湿延迟RWPN值较大,在大气相对稀薄的极地地区其值较小;同一测站的湿延迟RWPN具有明显的周年、半周年和季节性特征,极差值高达0.12 mm/√s以上;通过对ZWD残差值分析,发现ZWD残差信号除包含白噪声外,还具有4.8 h至2.43 d的高频信号分量。
基金The Natural Science Foundation of Jiangsu Province(No.BK2008429)Open Research Foundation of State Key Laboratory of Millimeter Waves of Southeast University(No.K200603)+1 种基金China Postdoctoral Science Foundation(No.20080431126)Jiangsu Postdoctoral Science Foundation(No.2007-337)
文摘A new approach to conductive electromagnetic interference （EMI） noise source modeling, i. e. the source internal impedance extraction, is presented. First, the impedance magnitude is achieved through an exciting probe and a detecting probe, or through calculations based on insertion loss measurement results when inserting a series nigh-value known impedance or a shunt low-value known impedance in the circuit. Then the impedance phase is extracted by the Hilbert transform （HT） of the logarithm of the obtained impedance magnitude. Performance studies show that the estimated phase error can increase greatly at a zero frequency in the Hilbert transform because of the existence of a singular point, and this effect can be eliminated by introducing a zero-point when the noise source does not include a series-connected capacitive component. It is also found that when the frequency is nigher than 150 kHz, the estimated phase error is not sensitive to the inductive source but sensitive to the capacitive source. Finally, under the conditions of the same measurement accuracies for impedance magnitude, the accuracy of complex impedance based on the HT can be improved about 10 times when compared with the accuracy of estimated parameters based on the impedance magnitude fitting method （IMFM）.
基金supported by the National Natural Science Foundation of China(Grant Nos.11172233,11272258,and 11302170)
文摘The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expression of the exit probability is obtained using the Taylor expansion and the infinitesimal generator theory. Based on numerical calculations, it is found that the immune delay facilitates tumor extinction when the stability index α〈 1, but inhibits tumor extinction when the stability index α 〉 1. Moreover, larger stability index and smaller noise intensity are in favor of the extinction for tumor with low density. While for tumor with high density, the stability index and the noise intensity should be reduced to promote tumor extinction.
