To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginnin...To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginning of adaptation the algorithmjust uses its current coefficient vector to update the adaptive filter to maintain fast convergence rate,while in steady state it employs several most recent coefficient vectors to update the adaptive filter to reduce misalignment. Simulation results showthat the proposed algorithmcan obtain both fast convergence rate and small steady-state misalignment.展开更多
The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to ...The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors （BVs） are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector （NLLV） scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram-Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more com- ponents in analysis errors than the BVs. In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model. The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random pertur- bation （RP） technique, and the BV method, as well as its improved version--the ensemble transform Kalman filter （ETKF） method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme.展开更多
Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter...Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter （EnKF） technology was used for the prediction of soil moisture in different soil layers： 0-5 cm, 30 cm, 50 cm, 100 cm, 200 cm, and 300 cm. The SVM methodology was first used to train the ground measurements of soil moisture and meteorological parameters from the Meilin study area, in East China, to construct soil moisture statistical prediction models. Subsequent observations and their statistics were used for predictions, with two approaches： the SVM predictor and the SVM-EnKF model made by coupling the SVM model with the EnKF technique using the DA method. Validation results showed that the proposed SVM-EnKF model can improve the prediction results of soil moisture in different layers, from the surface to the root zone.展开更多
Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products ...Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.展开更多
Usually the polarization of the interference and the target backscattering may vary constantly, so the optimal receiving polarization of the polarization filter should be recalculated, which makes the filter realizati...Usually the polarization of the interference and the target backscattering may vary constantly, so the optimal receiving polarization of the polarization filter should be recalculated, which makes the filter realization very difficult. Also the predict method of the necessary parameters is not explained in most papers, which makes the polarization filter realization impossible. A novel modi- fied interference suppression （MIS） polarization filter is proposed, which resolves these problems by a new polarization designed strategy. The computation of this polarization filter is easy in most conditions, and the necessary parameters estimation method in real time is introduced, which makes polarization filter design possible.展开更多
A novel digital implementation of speed controller for a Permanent Magnet Synchronous Motor (PMSM) with disturbance rejection using conventional observer combined with Extended Kalman Filter (EKF) is proposed. First, ...A novel digital implementation of speed controller for a Permanent Magnet Synchronous Motor (PMSM) with disturbance rejection using conventional observer combined with Extended Kalman Filter (EKF) is proposed. First, the EKF is constructed to achieve a precise estimation of the speed and current from the noisy measurement. Second, a proportional integral derivative (PID) controller is developed based on Linear Quadratic Regulator (LQR) to achieve speed command tracking performance. Then, an observer is designed and its error is utilized to provide load disturbance compensation. The proposed method greatly enhances the PMSM performance by reducing the control signal variation as well as the disturbance. The speed control performance is significantly improved compared to the case when we have an observer acting alone. The simulation results for the speed response and variation of the states when the PMSM is subjected to the load disturbance are presented. The results verify the effectiveness of the proposed method.展开更多
We theoretically investigate the wave-vector filtering(WVF)effect for electrons in an antiparallel asymmetric doubleδ-magnetic-barrier microstructure under a bias,which can be fabricated experimentally by patterning ...We theoretically investigate the wave-vector filtering(WVF)effect for electrons in an antiparallel asymmetric doubleδ-magnetic-barrier microstructure under a bias,which can be fabricated experimentally by patterning two asymmetric ferromagnetic(FM)stripes on the top and the bottom of GaAs/AlxGa1−xAs heterostructure,respectively.It is found that an appreciable WVF effect appears because of an essentially two-dimensional(2D)process for electrons across this microstructure.WVF effect is found to be sensitive to the applied bias.WVF efficiency can be tuned by changing bias,which may lead to an electrically-controllable momentum filter for nanoelectronics device applications.展开更多
A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acous...A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.展开更多
Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference...Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference tools for analyzing the behavior of this family of filters are presented. The proposed approach is based on the classification of color errors into two main classes that separately take into account the inaccuracy in removing noise pulses and the filtering distortion. The distortion errors are then classified into two subclasses for a deeper analysis of the filtering behavior. Computer simulations show that the proposed method gives more accurate results than using other measures of filtering performance in the literature. Furthermore, the method can easily yield the spatial location of the different filtering features in the image.展开更多
This paper investigates the problem of estimation of the wheelchair position in indoor environments with noisy mea- surements. The measuring system is based on two odometers placed on the axis of the wheels combined w...This paper investigates the problem of estimation of the wheelchair position in indoor environments with noisy mea- surements. The measuring system is based on two odometers placed on the axis of the wheels combined with a magnetic compass to determine the position and orientation. Determination of displacements is implemented by an accelerometer. Data coming from sensors are combined and used as inputs to unscented Kalman filter （UKF）. Two data fusion architectures： measurement fusion （MF） and state vector fusion （SVF） are proposed to merge the available measurements. Comparative studies of these two architectures show that the MF architecture provides states estimation with relatively less uncertainty compared to SVF. However, odometers measurements determine the position with relatively high uncertainty followed by the accelerometer measurements. Therefore, fusion in the navigation system is needed. The obtained simulation results show the effectiveness of proposed architectures.展开更多
Vehicle tracking plays a crucial role in intelligent transportation, autonomous driving, and video surveillance. However, challenges such as occlusion, multi-target interference, and nonlinear motion in dynamic scenar...Vehicle tracking plays a crucial role in intelligent transportation, autonomous driving, and video surveillance. However, challenges such as occlusion, multi-target interference, and nonlinear motion in dynamic scenarios make tracking accuracy and stability a focus of ongoing research. This paper proposes an integrated method combining YOLOv8 object detection with adaptive Kalman filtering. The approach employs a support vector machine (SVM) to dynamically select the optimal filter (including standard Kalman filter, extended Kalman filter, and unscented Kalman filter), enhancing the system’s adaptability to different motion patterns. Additionally, an error feedback mechanism is incorporated to dynamically adjust filter parameters, further improving responsiveness to sudden events. Experimental results on the KITTI and UA-DETRAC datasets demonstrate that the proposed method significantly improves detection accuracy (mAP@0.5 increased by approximately 3%), tracking accuracy (MOTA improved by 5%), and system robustness, providing an efficient solution for vehicle tracking in complex environments.展开更多
This paper presents a new system identification approach using vector space base functions, and proposes two network structures based on Gamma sequence and Laguerre sequence. After analyzing and comparing these struct...This paper presents a new system identification approach using vector space base functions, and proposes two network structures based on Gamma sequence and Laguerre sequence. After analyzing and comparing these structures in detail, some simulation results to demonstrate the conclusions are given.展开更多
基金Supported by the National Natural Science Foundation of China( 61471251 61101217)the Natural Science Foundation of Jiangsu Province of China (BK20131164)
文摘To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginning of adaptation the algorithmjust uses its current coefficient vector to update the adaptive filter to maintain fast convergence rate,while in steady state it employs several most recent coefficient vectors to update the adaptive filter to reduce misalignment. Simulation results showthat the proposed algorithmcan obtain both fast convergence rate and small steady-state misalignment.
文摘The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors （BVs） are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector （NLLV） scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram-Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more com- ponents in analysis errors than the BVs. In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model. The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random pertur- bation （RP） technique, and the BV method, as well as its improved version--the ensemble transform Kalman filter （ETKF） method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme.
基金supported by the National Basic Research Program of China (the 973 Program,Grant No.2010CB951101)the Program for Changjiang Scholars and Innovative Research Teams in Universities,the Ministry of Education,China (Grant No. IRT0717)
文摘Hybrid data assimilation （DA） is a method seeing more use in recent hydrology and water resources research. In this study, a DA method coupled with the support vector machines （SVMs） and the ensemble Kalman filter （EnKF） technology was used for the prediction of soil moisture in different soil layers： 0-5 cm, 30 cm, 50 cm, 100 cm, 200 cm, and 300 cm. The SVM methodology was first used to train the ground measurements of soil moisture and meteorological parameters from the Meilin study area, in East China, to construct soil moisture statistical prediction models. Subsequent observations and their statistics were used for predictions, with two approaches： the SVM predictor and the SVM-EnKF model made by coupling the SVM model with the EnKF technique using the DA method. Validation results showed that the proposed SVM-EnKF model can improve the prediction results of soil moisture in different layers, from the surface to the root zone.
基金Supported bythe Hunan Teaching Reformand Re-search Project of Colleges and Universities (2003-B72) the HunanBoard of Review on Philosophic and Social Scientific Pay-off Project(0406035) the Hunan Soft Science Research Project(04ZH6005)
文摘Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.
基金supported by the National Natural Science Foundation of China (60736001)
文摘Usually the polarization of the interference and the target backscattering may vary constantly, so the optimal receiving polarization of the polarization filter should be recalculated, which makes the filter realization very difficult. Also the predict method of the necessary parameters is not explained in most papers, which makes the polarization filter realization impossible. A novel modi- fied interference suppression （MIS） polarization filter is proposed, which resolves these problems by a new polarization designed strategy. The computation of this polarization filter is easy in most conditions, and the necessary parameters estimation method in real time is introduced, which makes polarization filter design possible.
文摘A novel digital implementation of speed controller for a Permanent Magnet Synchronous Motor (PMSM) with disturbance rejection using conventional observer combined with Extended Kalman Filter (EKF) is proposed. First, the EKF is constructed to achieve a precise estimation of the speed and current from the noisy measurement. Second, a proportional integral derivative (PID) controller is developed based on Linear Quadratic Regulator (LQR) to achieve speed command tracking performance. Then, an observer is designed and its error is utilized to provide load disturbance compensation. The proposed method greatly enhances the PMSM performance by reducing the control signal variation as well as the disturbance. The speed control performance is significantly improved compared to the case when we have an observer acting alone. The simulation results for the speed response and variation of the states when the PMSM is subjected to the load disturbance are presented. The results verify the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.11864009).
文摘We theoretically investigate the wave-vector filtering(WVF)effect for electrons in an antiparallel asymmetric doubleδ-magnetic-barrier microstructure under a bias,which can be fabricated experimentally by patterning two asymmetric ferromagnetic(FM)stripes on the top and the bottom of GaAs/AlxGa1−xAs heterostructure,respectively.It is found that an appreciable WVF effect appears because of an essentially two-dimensional(2D)process for electrons across this microstructure.WVF effect is found to be sensitive to the applied bias.WVF efficiency can be tuned by changing bias,which may lead to an electrically-controllable momentum filter for nanoelectronics device applications.
基金Sponsored by National Natural Foundation (50979093)the High Technology Research and Development Program of China (863 Program)( 2007AA809502C)Program for New Century Excellent Talents in University (NCET-06-0877)
文摘A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.
文摘Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference tools for analyzing the behavior of this family of filters are presented. The proposed approach is based on the classification of color errors into two main classes that separately take into account the inaccuracy in removing noise pulses and the filtering distortion. The distortion errors are then classified into two subclasses for a deeper analysis of the filtering behavior. Computer simulations show that the proposed method gives more accurate results than using other measures of filtering performance in the literature. Furthermore, the method can easily yield the spatial location of the different filtering features in the image.
文摘This paper investigates the problem of estimation of the wheelchair position in indoor environments with noisy mea- surements. The measuring system is based on two odometers placed on the axis of the wheels combined with a magnetic compass to determine the position and orientation. Determination of displacements is implemented by an accelerometer. Data coming from sensors are combined and used as inputs to unscented Kalman filter （UKF）. Two data fusion architectures： measurement fusion （MF） and state vector fusion （SVF） are proposed to merge the available measurements. Comparative studies of these two architectures show that the MF architecture provides states estimation with relatively less uncertainty compared to SVF. However, odometers measurements determine the position with relatively high uncertainty followed by the accelerometer measurements. Therefore, fusion in the navigation system is needed. The obtained simulation results show the effectiveness of proposed architectures.
文摘Vehicle tracking plays a crucial role in intelligent transportation, autonomous driving, and video surveillance. However, challenges such as occlusion, multi-target interference, and nonlinear motion in dynamic scenarios make tracking accuracy and stability a focus of ongoing research. This paper proposes an integrated method combining YOLOv8 object detection with adaptive Kalman filtering. The approach employs a support vector machine (SVM) to dynamically select the optimal filter (including standard Kalman filter, extended Kalman filter, and unscented Kalman filter), enhancing the system’s adaptability to different motion patterns. Additionally, an error feedback mechanism is incorporated to dynamically adjust filter parameters, further improving responsiveness to sudden events. Experimental results on the KITTI and UA-DETRAC datasets demonstrate that the proposed method significantly improves detection accuracy (mAP@0.5 increased by approximately 3%), tracking accuracy (MOTA improved by 5%), and system robustness, providing an efficient solution for vehicle tracking in complex environments.
基金National Natural Science FundsNatural Science Funds of Jiangsu Province
文摘This paper presents a new system identification approach using vector space base functions, and proposes two network structures based on Gamma sequence and Laguerre sequence. After analyzing and comparing these structures in detail, some simulation results to demonstrate the conclusions are given.
