This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter mod...This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.展开更多
In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristi...In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.展开更多
For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to ...For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to estimate the approximative covariance matrix in the non-homogeneous condition. According to the statistical characteristics of the space-time snapshot data, via defining the aggregate snapshot data and corresponding events, the conditional probability of the space-time snapshot data which is the effective training data is given, then the weighting coefficients are obtained for the weighting method. The theory analysis indicates that the statistical methods of the Bayes and likelihood criterion for covariance matrix estimation are more reasonable than other methods that estimate the covariance matrix with the use of training data except the detected outliers. The last simulations attest that the proposed algorithms can estimate the covariance in the non-homogeneous condition exactly and have favorable characteristics.展开更多
This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant...This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant-Block(BCCB)preconditioner is constructed.Based on thepreconditioner,a Preconditioned Multistage Wiener Filter(PMWF)which can be implemented by thePreconditioned Conjugate Gradient(PCG)method is proposed.Simulation results show that thePMWF has faster convergence rate and lower processing rank compared with the MWF.展开更多
A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon a...A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.展开更多
As a new research direction in contemporary cognitive science,predictive processing surpasses traditional computational representation and embodied cognition and has emerged as a new paradigm in cognitive science rese...As a new research direction in contemporary cognitive science,predictive processing surpasses traditional computational representation and embodied cognition and has emerged as a new paradigm in cognitive science research.The predictive processing theory advocates that the brain is a hierarchical predictive model based on Bayesian inference,and its purpose is to minimize the difference between the predicted world and the actual world,so as to minimize the prediction error.Predictive processing is therefore essentially a context-dependent model representation,an adaptive representational system designed to achieve its cognitive goals through the minimization of prediction error.展开更多
A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar sy...A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar systems which includes most of suboptimum algorithms in the literature is proposed. The performance of two typical rank-reduced time-space joint-domain processors based on Doppler pre-filtering is analyzed in detail based on the proposed framework.展开更多
Underwater monopulse space-time adaptive track-before-detect method,which combines space-time adaptive detector(STAD)and the track-before-detect algorithm based on dynamic programming(DP-TBD),denoted as STAD-DP-TBD,ca...Underwater monopulse space-time adaptive track-before-detect method,which combines space-time adaptive detector(STAD)and the track-before-detect algorithm based on dynamic programming(DP-TBD),denoted as STAD-DP-TBD,can effectively detect low-speed weak targets.However,due to the complexity and variability of the underwater environment,it is difficult to obtain sufficient secondary data,resulting in a serious decline in the detection and tracking performance,and leading to poor robustness of the algorithm.In this paper,based on the adaptive matched filter(AMF)test and the RAO test,underwater monopulse AMF-DP-TBD algorithm and RAO-DP-TBD algorithm which incorporate persymmetry and symmetric spectrum,denoted as PSAMF-DP-TBD and PS-RAO-DP-TBD,are proposed and compared with the AMF-DP-TBD algorithm and RAO-DP-TBD algorithm based on persymmetry array,denoted as P-AMF-DP-TBD and P-RAO-DP-TBD.The simulation results show that the four methods can work normally with sufficient secondary data and slightly insufficient secondary data,but when the secondary data is severely insufficient,the P-AMF-DP-TBD and P-RAO-DP-TBD algorithms has failed while the PSAMF-DP-TBD and PS-RAO-DP-TBD algorithms still have good detection and tracking capabilities.展开更多
To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two...To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two array errors is proposed in this article.First,based on a defined error matrix that simultaneously considers both array mutual coupling and gain/phase errors,a STAP signal model including these errors is given.Then,utilizing the defined signal model,it is demonstrated that the estimation of the defined error matrix can be formulized as a standard convex optimization problem with the low-rank structure of the clutter covariance matrix and the subspace projection theory.Once the defined error matrix is estimated by solving the convex optimization problem,it is illustrated that a STAP method with adaptive calibration of the mutual coupling and gain/phase errors is coined.Analyses also show that the proposed adaptive calibration algorithm only needs one training sample to construct the adaptive weight vector.Therefore,it can achieve a good detection performance even with severe non-homogeneous clutter environments.Finally,the simulation experiments verify the effectiveness of the proposed algorithm and the correctness of the analytical results.展开更多
A method of space-time block coding （STBC） system based on adaptive beamforming of cyclostationarity signal algorithm is proposed.The method uses cyclostationarity of signals to achieve adaptive beamforming,then con...A method of space-time block coding （STBC） system based on adaptive beamforming of cyclostationarity signal algorithm is proposed.The method uses cyclostationarity of signals to achieve adaptive beamforming,then constructs a pair of low correlated transmit beams based on beamform estimation of multiple component signals of uplink.Using these two selected transmit beams,signals encoded by STBC are transmitted to achieve diversity gain and beamforming gain at the same time,and increase the signal to noise ratio （SNR） of downlink.With simple computation and fast convergence performance,the proposed scheme is applicable for time division multiple access （TDMA） wireless communication operated in a complex interference environment.Simulation results show that the proposed scheme has better performance than conventional STBC,and can obtain a gain of about 5 dB when the bit error ratio （BER） is 10-4.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation indust...Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.展开更多
In wastewater treatment systems,extracting meaningful features from process data is essential for effective monitoring and control.However,the multi-time scale data generated by different sampling frequencies pose a c...In wastewater treatment systems,extracting meaningful features from process data is essential for effective monitoring and control.However,the multi-time scale data generated by different sampling frequencies pose a challenge to accurately extract features.To solve this issue,a multi-timescale feature extraction method based on adaptive entropy is proposed.Firstly,the expert knowledge graph is constructed by analyzing the characteristics of wastewater components and water quality data,which can illustrate various water quality parameters and the network of relationships among them.Secondly,multiscale entropy analysis is used to investigate the inherent multi-timescale patterns of water quality data in depth,which enables us to minimize information loss while uniformly optimizing the timescale.Thirdly,we harness partial least squares for feature extraction,resulting in an enhanced representation of sample data and the iterative enhancement of our expert knowledge graph.The experimental results show that the multi-timescale feature extraction algorithm can enhance the representation of water quality data and improve monitoring capabilities.展开更多
In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the ne...In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point.The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control(MFAC)method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters.Then the convergence and stability of the MFAC-SA-PID method are proved in this paper.In the simulation study,the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control(IMFAC)method,respectively.The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process.The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added,which indicates that the MFAC-SA-PID method has better robustness and stability.展开更多
In H.264,computational complexity and memory access of deblocking filters are variable,dependent on video contents.This paper proposes a VLSI architecture of deblocking filters with adaptive dynamic power,which avoids...In H.264,computational complexity and memory access of deblocking filters are variable,dependent on video contents.This paper proposes a VLSI architecture of deblocking filters with adaptive dynamic power,which avoids redundant computations and memory accesses by precluding the blocks that can be skipped.The vertical and horizontal edges are simulta-neously processed in an advanced scan order to speed up the decoder.As a result,dynamic power of the proposed architecture can be reduced adaptively(up to about 89%) for different videos,and the off-chip memory access is improved when compared to previous designs.Moreover,the processing capability of the proposed architecture is in particular appropriate for real-time deblocking of high-definition television(HDTV,1920×1080 pixels/frame,60 frames/s video signals) video operation at 62 MHz.Using the proposed architecture,power can be reduced by up to about 89% and processing time by from 25% to 81% compared with previous designs.展开更多
To satisfy the request of wireless communication for new generation communication system, a new scheme consisting of a combination of adaptive technology and space-time code-OFDM is presented. The proposed method, exp...To satisfy the request of wireless communication for new generation communication system, a new scheme consisting of a combination of adaptive technology and space-time code-OFDM is presented. The proposed method, exploits adaptive bit allocation scheme over multipath fading channel. Numerical simulations have shown that the proposed scheme can greatly improve the performance of non-adaptive STBC-OFDM system.展开更多
Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity.The goal of this work is to in...Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity.The goal of this work is to inves-tigate the use of fractional order algorithm in the field of adaptive beam-forming,with a focus on improving performance while keeping complexity lower.The effectiveness of the algorithm will be studied and evaluated in this context.In this paper,a fractional order least mean square(FLMS)algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of resources.This algorithm aims to improve upon existing beam-forming algorithms,which are inefficient in performance,by offering faster convergence,better accuracy,and comparable computational complexity.The FLMS algorithm uses fractional order gradient in addition to the standard ordered gradient in weight adaptation.The derivation of the algorithm is provided and supported by mathematical convergence analysis.Performance is evaluated through simulations using mean square error(MSE)minimization as a metric and compared with the standard LMS algorithm for various parameters.The results,obtained through Matlab simulations,show that the FLMS algorithm outperforms the standard LMS in terms of convergence speed,beampattern accuracy and scatter plots.FLMS outperforms LMS in terms of convergence speed by 34%.From this,it can be concluded that FLMS is a better candidate for adaptive beamforming and other signal processing applications.展开更多
A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer syste...A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.展开更多
The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and...The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process展开更多
Low stiffness and positioning problems are difficulties and challenges in the precise machining of near-net-shaped blades.This paper aims to achieve high accuracy in manufacturing by fixture-and deformation-control in...Low stiffness and positioning problems are difficulties and challenges in the precise machining of near-net-shaped blades.This paper aims to achieve high accuracy in manufacturing by fixture-and deformation-control in the adaptive CNC machining process.Adaptive CNC machining technology is first analyzed,and new fixture-evaluation criteria and methods to evaluate the adaptive CNC machining process fixture design are built.Second,a machining fixture is designed and manufactured after analyzing its positioning scheme,clamping scheme,materials(PEEK-GF30),and structure characteristics.Finally,the designed fixture is analyzed by FEA and experimentally verified by a cutting experiment.The results show that the deformation of the blade is an overall rigid-body displacement,the main deformation of the blade-fixture system occurs on the four clamping heads,and this fixture can effectively protect the blade from local deformation.The proposed clamping-sequence method reliably and effectively controls the local maximum deformation of the blade.The system stiffness is increased by 20 Hz,with each clamping force increased by 200 N.Both high-and low-frequency displacement in roughing milling or finishing milling are acceptable relative to the accuracy demand of blade machining.This fixture and an adaptive CNC machining process can achieve high accuracy in blade manufacturing.展开更多
基金supported by the National Natural Science Foundation of China(60901056)
文摘This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.
文摘In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.
基金Supported by the National Post-doctor Fundation (No. 20090451251) the Shaanxi Industry Surmount Foundation (2009K08-31) of China
文摘For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to estimate the approximative covariance matrix in the non-homogeneous condition. According to the statistical characteristics of the space-time snapshot data, via defining the aggregate snapshot data and corresponding events, the conditional probability of the space-time snapshot data which is the effective training data is given, then the weighting coefficients are obtained for the weighting method. The theory analysis indicates that the statistical methods of the Bayes and likelihood criterion for covariance matrix estimation are more reasonable than other methods that estimate the covariance matrix with the use of training data except the detected outliers. The last simulations attest that the proposed algorithms can estimate the covariance in the non-homogeneous condition exactly and have favorable characteristics.
基金the Innovation Foundation of NUDT forPh.D.graduates.
文摘This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant-Block(BCCB)preconditioner is constructed.Based on thepreconditioner,a Preconditioned Multistage Wiener Filter(PMWF)which can be implemented by thePreconditioned Conjugate Gradient(PCG)method is proposed.Simulation results show that thePMWF has faster convergence rate and lower processing rank compared with the MWF.
基金National Nature Science FoundationNational Deferise Research Funds
文摘A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.
基金supported by the National Social Science Fund of China’s project‘Philosophical Research on the Challenge of Artificial Cognition to Natural Cognition’(grant number 21&ZD061)
文摘As a new research direction in contemporary cognitive science,predictive processing surpasses traditional computational representation and embodied cognition and has emerged as a new paradigm in cognitive science research.The predictive processing theory advocates that the brain is a hierarchical predictive model based on Bayesian inference,and its purpose is to minimize the difference between the predicted world and the actual world,so as to minimize the prediction error.Predictive processing is therefore essentially a context-dependent model representation,an adaptive representational system designed to achieve its cognitive goals through the minimization of prediction error.
基金Project supported by the Foundation of Key Laboratory for Radar Signal Processing.
文摘A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar systems which includes most of suboptimum algorithms in the literature is proposed. The performance of two typical rank-reduced time-space joint-domain processors based on Doppler pre-filtering is analyzed in detail based on the proposed framework.
基金supported by the National Natural Science Foundation of China (No.61971412)。
文摘Underwater monopulse space-time adaptive track-before-detect method,which combines space-time adaptive detector(STAD)and the track-before-detect algorithm based on dynamic programming(DP-TBD),denoted as STAD-DP-TBD,can effectively detect low-speed weak targets.However,due to the complexity and variability of the underwater environment,it is difficult to obtain sufficient secondary data,resulting in a serious decline in the detection and tracking performance,and leading to poor robustness of the algorithm.In this paper,based on the adaptive matched filter(AMF)test and the RAO test,underwater monopulse AMF-DP-TBD algorithm and RAO-DP-TBD algorithm which incorporate persymmetry and symmetric spectrum,denoted as PSAMF-DP-TBD and PS-RAO-DP-TBD,are proposed and compared with the AMF-DP-TBD algorithm and RAO-DP-TBD algorithm based on persymmetry array,denoted as P-AMF-DP-TBD and P-RAO-DP-TBD.The simulation results show that the four methods can work normally with sufficient secondary data and slightly insufficient secondary data,but when the secondary data is severely insufficient,the P-AMF-DP-TBD and P-RAO-DP-TBD algorithms has failed while the PSAMF-DP-TBD and PS-RAO-DP-TBD algorithms still have good detection and tracking capabilities.
基金co-supported by the National Natural Science Foundation of China(No.12374431)。
文摘To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two array errors is proposed in this article.First,based on a defined error matrix that simultaneously considers both array mutual coupling and gain/phase errors,a STAP signal model including these errors is given.Then,utilizing the defined signal model,it is demonstrated that the estimation of the defined error matrix can be formulized as a standard convex optimization problem with the low-rank structure of the clutter covariance matrix and the subspace projection theory.Once the defined error matrix is estimated by solving the convex optimization problem,it is illustrated that a STAP method with adaptive calibration of the mutual coupling and gain/phase errors is coined.Analyses also show that the proposed adaptive calibration algorithm only needs one training sample to construct the adaptive weight vector.Therefore,it can achieve a good detection performance even with severe non-homogeneous clutter environments.Finally,the simulation experiments verify the effectiveness of the proposed algorithm and the correctness of the analytical results.
文摘A method of space-time block coding （STBC） system based on adaptive beamforming of cyclostationarity signal algorithm is proposed.The method uses cyclostationarity of signals to achieve adaptive beamforming,then constructs a pair of low correlated transmit beams based on beamform estimation of multiple component signals of uplink.Using these two selected transmit beams,signals encoded by STBC are transmitted to achieve diversity gain and beamforming gain at the same time,and increase the signal to noise ratio （SNR） of downlink.With simple computation and fast convergence performance,the proposed scheme is applicable for time division multiple access （TDMA） wireless communication operated in a complex interference environment.Simulation results show that the proposed scheme has better performance than conventional STBC,and can obtain a gain of about 5 dB when the bit error ratio （BER） is 10-4.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
基金supported in part by the National Key Research and Development Program of China(2021YFC2902703)the National Natural Science Foundation of China(62173078,61773105,61533007,61873049,61873053,61703085,61374147)。
文摘Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.
基金the National Key Research and Development Program of China(2022YFB3305800-5)the National Natural Science Foundation of China(62125301,62021003)+2 种基金the Beijing Outstanding Young Scientist Program(BJJWZYJH01201910005020)the Natural Science Foundation of Beijing Municipality(KZ202110005009)Youth Beijing Scholar(037).
文摘In wastewater treatment systems,extracting meaningful features from process data is essential for effective monitoring and control.However,the multi-time scale data generated by different sampling frequencies pose a challenge to accurately extract features.To solve this issue,a multi-timescale feature extraction method based on adaptive entropy is proposed.Firstly,the expert knowledge graph is constructed by analyzing the characteristics of wastewater components and water quality data,which can illustrate various water quality parameters and the network of relationships among them.Secondly,multiscale entropy analysis is used to investigate the inherent multi-timescale patterns of water quality data in depth,which enables us to minimize information loss while uniformly optimizing the timescale.Thirdly,we harness partial least squares for feature extraction,resulting in an enhanced representation of sample data and the iterative enhancement of our expert knowledge graph.The experimental results show that the multi-timescale feature extraction algorithm can enhance the representation of water quality data and improve monitoring capabilities.
基金supported by the National Natural Science Foundation of China(61771034).
文摘In this paper,a new model free adaptive control method based on self-adjusting PID algorithm(MFACSA-PID)is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point.The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control(MFAC)method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters.Then the convergence and stability of the MFAC-SA-PID method are proved in this paper.In the simulation study,the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control(IMFAC)method,respectively.The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process.The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added,which indicates that the MFAC-SA-PID method has better robustness and stability.
基金Project (No. NSS’USA5978) supported by the National Science Foundation of the United States under the East Asia Pacific Program
文摘In H.264,computational complexity and memory access of deblocking filters are variable,dependent on video contents.This paper proposes a VLSI architecture of deblocking filters with adaptive dynamic power,which avoids redundant computations and memory accesses by precluding the blocks that can be skipped.The vertical and horizontal edges are simulta-neously processed in an advanced scan order to speed up the decoder.As a result,dynamic power of the proposed architecture can be reduced adaptively(up to about 89%) for different videos,and the off-chip memory access is improved when compared to previous designs.Moreover,the processing capability of the proposed architecture is in particular appropriate for real-time deblocking of high-definition television(HDTV,1920×1080 pixels/frame,60 frames/s video signals) video operation at 62 MHz.Using the proposed architecture,power can be reduced by up to about 89% and processing time by from 25% to 81% compared with previous designs.
文摘To satisfy the request of wireless communication for new generation communication system, a new scheme consisting of a combination of adaptive technology and space-time code-OFDM is presented. The proposed method, exploits adaptive bit allocation scheme over multipath fading channel. Numerical simulations have shown that the proposed scheme can greatly improve the performance of non-adaptive STBC-OFDM system.
基金supported by the Office of Research and Innovation(IRG project#23207)at Alfaisal University,Riyadh,KSA.
文摘Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity.The goal of this work is to inves-tigate the use of fractional order algorithm in the field of adaptive beam-forming,with a focus on improving performance while keeping complexity lower.The effectiveness of the algorithm will be studied and evaluated in this context.In this paper,a fractional order least mean square(FLMS)algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of resources.This algorithm aims to improve upon existing beam-forming algorithms,which are inefficient in performance,by offering faster convergence,better accuracy,and comparable computational complexity.The FLMS algorithm uses fractional order gradient in addition to the standard ordered gradient in weight adaptation.The derivation of the algorithm is provided and supported by mathematical convergence analysis.Performance is evaluated through simulations using mean square error(MSE)minimization as a metric and compared with the standard LMS algorithm for various parameters.The results,obtained through Matlab simulations,show that the FLMS algorithm outperforms the standard LMS in terms of convergence speed,beampattern accuracy and scatter plots.FLMS outperforms LMS in terms of convergence speed by 34%.From this,it can be concluded that FLMS is a better candidate for adaptive beamforming and other signal processing applications.
文摘A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.
基金the Key Technologies R&D Program of Harbin (0111211102).
文摘The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process
基金supported in part by Xi’an Aero-Engine(Group)Ltd.National Key Scientific Instrument and Equipment Development Project(2016YFF0101900)+1 种基金National Natural Science Foundation of China(Grant 51575310)Beijing Municipal Natural Science Foundation(Grant 3162014)。
文摘Low stiffness and positioning problems are difficulties and challenges in the precise machining of near-net-shaped blades.This paper aims to achieve high accuracy in manufacturing by fixture-and deformation-control in the adaptive CNC machining process.Adaptive CNC machining technology is first analyzed,and new fixture-evaluation criteria and methods to evaluate the adaptive CNC machining process fixture design are built.Second,a machining fixture is designed and manufactured after analyzing its positioning scheme,clamping scheme,materials(PEEK-GF30),and structure characteristics.Finally,the designed fixture is analyzed by FEA and experimentally verified by a cutting experiment.The results show that the deformation of the blade is an overall rigid-body displacement,the main deformation of the blade-fixture system occurs on the four clamping heads,and this fixture can effectively protect the blade from local deformation.The proposed clamping-sequence method reliably and effectively controls the local maximum deformation of the blade.The system stiffness is increased by 20 Hz,with each clamping force increased by 200 N.Both high-and low-frequency displacement in roughing milling or finishing milling are acceptable relative to the accuracy demand of blade machining.This fixture and an adaptive CNC machining process can achieve high accuracy in blade manufacturing.
