This paper considers a problem of unsupervised spectral unmixing of hyperspectral data. Based on the Linear Mixing Model （ LMM）, a new method under the framework of nonnegative matrix fac- torization （NMF） is prop...This paper considers a problem of unsupervised spectral unmixing of hyperspectral data. Based on the Linear Mixing Model （ LMM）, a new method under the framework of nonnegative matrix fac- torization （NMF） is proposed, namely minimum distance constrained nonnegative matrix factoriza- tion （MDC-NMF）. In this paper, firstly, a new regularization term, called endmember distance （ED） is considered, which is defined as the sum of the squared Euclidean distances from each end- member to their geometric center. Compared with the simplex volume, ED has better optimization properties and is conceptually intuitive. Secondly, a projected gradient （PG） scheme is adopted, and by the virtue of ED, in this scheme the optimal step size along the feasible descent direction can be calculated easily at each iteration. Thirdly, a finite step （ no more than the number of endmem- bers） terminated algorithm is used to project a point on the canonical simplex, by which the abun- dance nonnegative constraint and abundance sum-to-one constraint can be accurately satisfied in a light amount of computation. The experimental results, based on a set of synthetic data and real da- ta, demonstrate that, in the same running time, MDC-NMF outperforms several other similar meth- ods proposed recently.展开更多
Due to global energy depletion,solar energy technology has been widely used in the world.The output power of the solar energy systems is affected by solar radiation.Accurate short-term forecasting of solar radiation c...Due to global energy depletion,solar energy technology has been widely used in the world.The output power of the solar energy systems is affected by solar radiation.Accurate short-term forecasting of solar radiation can ensure the safety of photovoltaic grids and improve the utilization efficiency of the solar energy systems.In the study,a new decomposition-boosting model using artificial intelligence is proposed to realize the solar radiation multi-step prediction.The proposed model includes four parts:signal decomposition(EWT),neural network(NARX),Adaboost and ARIMA.Three real solar radiation datasets from Changde,China were used to validate the efficiency of the proposed model.To verify the robustness of the multi-step prediction model,this experiment compared nine models and made 1,3,and 5 steps ahead predictions for the time series.It is verified that the proposed model has the best performance among all models.展开更多
This paper describes two single-chip——complex programmable logic devices/field programmable gate arrays(CPLD/FPGA)——implementations of the new advanced encryption standard (AES) algorithm based on the basic iterat...This paper describes two single-chip——complex programmable logic devices/field programmable gate arrays(CPLD/FPGA)——implementations of the new advanced encryption standard (AES) algorithm based on the basic iteration architecture (design [A]) and the hybrid pipelining architecture (design [B]). Design [A] is an encryption-and-decryption implementation based on the basic iteration architecture. This design not only supports 128-bit, 192-bit, 256-bit keys, but saves hardware resources because of the iteration architecture and sharing technology. Design [B] is a method of the 2×2 hybrid pipelining architecture. Based on the AES interleaved mode of operation, the design successfully accomplishes the algorithm, which operates in the feedback mode (cipher block chaining). It not only guarantees security of encryption/decryption, but obtains high data throughput of 1.05 Gb/s. The two designs have been realized on Aitera′s EP20k300EBC652-1 devices.展开更多
The analytic-numerical hybrid model for calculating welding distortions in large welded structures is presented. Objective of the analytical model is the calculation of the plastic strains and their distribution after...The analytic-numerical hybrid model for calculating welding distortions in large welded structures is presented. Objective of the analytical model is the calculation of the plastic strains and their distribution after welding and thermal straightening process. The consideration of the essential physical relations is put into discussion. Afterwards the obtained plastic strains by the analytical calculation are loaded on an elastic FE-model of the structure and the distortions of the whole structure are predicted. The consideration of welding and thermal straightening scenarios and the assembling stages is done by taking into account the intermediate variation of the strain state at every processing step. The model is intended to be used for solving industrial tasks, i.e. intending acceptable precision and calculation time as well as low simulation costs. The application of the model is demonstrated on structures with many welds and straightening spots.展开更多
A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For ...A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.展开更多
As an advanced generation instrument of earth observation,small footprint full waveform light detection and ranging(LiDAR) technology has been widely used in the past few years.Decomposition and radiative correction i...As an advanced generation instrument of earth observation,small footprint full waveform light detection and ranging(LiDAR) technology has been widely used in the past few years.Decomposition and radiative correction is an important step in waveform data processing,it influences the accuracy of both information extraction and further applications.Based on a stepwise strategy,this study adopts Gaussian mixture model to approximate the LiDAR waveform.In addition to waveform decomposition,a relative correction model is proposed in this paper,the model considers the transmit pulses as well as the different of the travel path for implementing LiDAR waveform relative correction.Validation of the stepwise decomposition and relative correction model are carried out on LiDAR waveform acquired over Zhangye,China.The results indicate that stepwise decomposition identified the number of peaks in LiDAR waveforms,center position and width of each peak well.The relative radiometric correction also improves the similarity of waveforms which acquired at the same target.展开更多
基金Supported by the National Natural Science Foundation of China （ No. 60872083 ） and the National High Technology Research and Development Program of China （No. 2007AA12Z149）.
文摘This paper considers a problem of unsupervised spectral unmixing of hyperspectral data. Based on the Linear Mixing Model （ LMM）, a new method under the framework of nonnegative matrix fac- torization （NMF） is proposed, namely minimum distance constrained nonnegative matrix factoriza- tion （MDC-NMF）. In this paper, firstly, a new regularization term, called endmember distance （ED） is considered, which is defined as the sum of the squared Euclidean distances from each end- member to their geometric center. Compared with the simplex volume, ED has better optimization properties and is conceptually intuitive. Secondly, a projected gradient （PG） scheme is adopted, and by the virtue of ED, in this scheme the optimal step size along the feasible descent direction can be calculated easily at each iteration. Thirdly, a finite step （ no more than the number of endmem- bers） terminated algorithm is used to project a point on the canonical simplex, by which the abun- dance nonnegative constraint and abundance sum-to-one constraint can be accurately satisfied in a light amount of computation. The experimental results, based on a set of synthetic data and real da- ta, demonstrate that, in the same running time, MDC-NMF outperforms several other similar meth- ods proposed recently.
基金Project(2020TJ-Q06)supported by Hunan Provincial Science&Technology Talent Support,ChinaProject(KQ1707017)supported by the Changsha Science&Technology,ChinaProject(2019CX005)supported by the Innovation Driven Project of the Central South University,China。
文摘Due to global energy depletion,solar energy technology has been widely used in the world.The output power of the solar energy systems is affected by solar radiation.Accurate short-term forecasting of solar radiation can ensure the safety of photovoltaic grids and improve the utilization efficiency of the solar energy systems.In the study,a new decomposition-boosting model using artificial intelligence is proposed to realize the solar radiation multi-step prediction.The proposed model includes four parts:signal decomposition(EWT),neural network(NARX),Adaboost and ARIMA.Three real solar radiation datasets from Changde,China were used to validate the efficiency of the proposed model.To verify the robustness of the multi-step prediction model,this experiment compared nine models and made 1,3,and 5 steps ahead predictions for the time series.It is verified that the proposed model has the best performance among all models.
文摘This paper describes two single-chip——complex programmable logic devices/field programmable gate arrays(CPLD/FPGA)——implementations of the new advanced encryption standard (AES) algorithm based on the basic iteration architecture (design [A]) and the hybrid pipelining architecture (design [B]). Design [A] is an encryption-and-decryption implementation based on the basic iteration architecture. This design not only supports 128-bit, 192-bit, 256-bit keys, but saves hardware resources because of the iteration architecture and sharing technology. Design [B] is a method of the 2×2 hybrid pipelining architecture. Based on the AES interleaved mode of operation, the design successfully accomplishes the algorithm, which operates in the feedback mode (cipher block chaining). It not only guarantees security of encryption/decryption, but obtains high data throughput of 1.05 Gb/s. The two designs have been realized on Aitera′s EP20k300EBC652-1 devices.
文摘The analytic-numerical hybrid model for calculating welding distortions in large welded structures is presented. Objective of the analytical model is the calculation of the plastic strains and their distribution after welding and thermal straightening process. The consideration of the essential physical relations is put into discussion. Afterwards the obtained plastic strains by the analytical calculation are loaded on an elastic FE-model of the structure and the distortions of the whole structure are predicted. The consideration of welding and thermal straightening scenarios and the assembling stages is done by taking into account the intermediate variation of the strain state at every processing step. The model is intended to be used for solving industrial tasks, i.e. intending acceptable precision and calculation time as well as low simulation costs. The application of the model is demonstrated on structures with many welds and straightening spots.
基金Supported by the National High Technology Research and Development Programme of China （No. 2006AA04Z160） and the National Natural Science Foundation of China （ No. 60874066）.
文摘A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.
基金supported by Major State Basic Research Development Program of China(Grant No.2007CB714406)National Key Technology R&D Program of China(Grant No.2008BAC34B03)
文摘As an advanced generation instrument of earth observation,small footprint full waveform light detection and ranging(LiDAR) technology has been widely used in the past few years.Decomposition and radiative correction is an important step in waveform data processing,it influences the accuracy of both information extraction and further applications.Based on a stepwise strategy,this study adopts Gaussian mixture model to approximate the LiDAR waveform.In addition to waveform decomposition,a relative correction model is proposed in this paper,the model considers the transmit pulses as well as the different of the travel path for implementing LiDAR waveform relative correction.Validation of the stepwise decomposition and relative correction model are carried out on LiDAR waveform acquired over Zhangye,China.The results indicate that stepwise decomposition identified the number of peaks in LiDAR waveforms,center position and width of each peak well.The relative radiometric correction also improves the similarity of waveforms which acquired at the same target.
