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第35届中国控制会议

作者： WANG Shiyuan ZHENG Yunfei DUAN Shukai College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

ISBN: (纸本)9781509009107

The Huber adaptive filter is robust both in the Gaussian and non-Gaussian noise *** correntropy induced metric（CIM） is an excellent approximator of the l-norm and can be used as a sparsity penalty ***,a novel sparse method based on the Huber cost with CIM constraint（CIM-Huber） is developed for sparse system identification in this *** comparison,the Huber cost functions with zero-attracting penalty（ZA-Huber） and reweighted zero-attracting penalty（RZA-Huber） algorithm are discussed *** results show that the proposed CIM-Huber has a better performance in the identification of sparse systems than the ZA-Huber and the RZA-Huber,and can also be applied to system identification under the cases of various noise environments.

关键词： Sparse system identification Huber adaptive filter Correntropy induced metric Noise

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A simple motion deblurring method by two continuous images 6

A simple motion deblurring method by two continuous images

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6th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2019

作者： Zhang, Jihai Li, Jianfeng Liu, Guangyuan Chen, Tong Zhu, Tengteng Li, Bo Chongqing Key Laboratory of Nonlinear Circuits Intelligent Information Processing Chongqing400715 China

ISBN: (纸本)9781728158570

Restoring blurred images to clear images is a challenging problem. Most previous methods only analyzed the single image. However, for motion blurring, this method missed the key trajectory description process. Based on the essence of motion blur, our research combined the continuous frame image information in video to estimate the motion track, the SIFT algorithm was proposed for the first time to match the feature points of the target in the continuous frame image. The accurate motion blur angle and motion blur distance were obtained by combining the matching information to obtain an accurate PSF. Finally, the Wiener filtering algorithm combined with PSF was used for deblurring. Experiments showed that the proposed method can improve the image sharpness after restoration compared with the previous algorithms. © 2019 IEEE.

关键词： Image enhancement

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Application of multiple two-dimensional interpolation methods to bathymetric data on the FVCOM unstructured triangular grid

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Applied Mathematics and Computation 2025年 507卷

作者： Zongli Ruan Guobing Qian Yiwei Wang Jia Xiao College of Science China University of Petroleum (East China) Qingdao 266580 PR China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing 400715 PR China

In general, the ocean bathymetric dataset is defined on a uniform rectangular grid, whereas FVCOM employs an unstructured triangular grid. Consequently, it is necessary to interpolate the data from the nodes of the rectangular grid onto those of the triangular grid. The nearest neighbor method, bilinear method, and inverse distance weighting (IDW) method are three commonly utilized two-dimensional interpolation techniques, and inverse distance weighted regression (IDWR) represents a more recent interpolation approach. In this study, these methods were applied to interpolate the bathymetric data of the Hormuz Strait and the North Indian Ocean onto the FVCOM triangular grid. The experimental results demonstrate that a very small error in the interpolation of bathymetric data was achieved. Additionally, these methods were compared with the interpolation techniques provided by the MATLAB system. The comparative analysis reveals that the bilinear method can achieve a superior interpolation effect compared to the other three methods.

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ISS -equilibrium with stability analysis for disturbed game-based impulsive systems

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Automatica 2025年 179卷

作者： Wenlu Liu Chuandong Li Xiaodi Li Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing 400715 PR China School of Mathematics and Statistics Shandong Normal University Ji’nan 250014 PR China

This paper focuses on a class of two-player differential games subject to exogenous disturbances, where one player employs piecewise-continuous control, and the other uses impulsive control. Particularly, the exploration of equilibrium solution in differential games is accompanied by the stability performance analysis of relevant system. To be more specific, the construction of saddle point in zero-sum differential game and Nash equilibrium in nonzero-sum differential game is established under the Lyapunov criteria for input-to-state stability ( ISS ). Furthermore, owing to the existence of external disturbances and the characterization of ISS property, two extended equilibrium solution concepts are introduced. We propose the definition of ϵ - ISS saddle point and ϵ - ISS Nash equilibrium for which the corresponding verification theorems are formulated. Finally, two numerical experiments are provided to illustrate the proposed results.

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A Read and Write Method for Forgetting Memristor Crossbar Array with Long-term and Short-term Memory

A Read and Write Method for Forgetting Memristor Crossbar Ar...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Wang, Yifan Chen, Ling Li, Chuandong College of Westa Chongqing Southwest University Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China College of Electronic Information and Engineering Chongqing Southwest University Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (纸本)9781665412872

In this paper, time slot technology is designed based on the single forgetting memristor synapse with single voltage source to read and write the forgetting memristor crossbar array. The amplitude of the voltage source signal is used to set the corresponding long-term and short-term memory weights, and the circuit protection signal is used to improve the security of the nanoscale memristor crossbar array. By analyzing the forgetting properties of memristor synapses, the forgetting memristor crossbar array with long-term memory, short-term memory (LSM) and its corresponding read-write mode are demonstrated. Because the forgetting memristor crossbar array can store both long-term and short-term memories, the application of forgetting memristor crossbar array to image storage can show the spontaneous evolution of images. © 2021 IEEE.

关键词： Memristors

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Event-Triggered Differentially Private Average Consensus for Multi-agent Network

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 75-83页

作者： Aijuan Wang Xiaofeng Liao Haibo He the College of Computer Science Chongqing University the School of Electronics and Information Engineering Southwest University the Department of Electrical Computer and Biomedical EngineeringUniversity of Rhode Island Kingston IEEE Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing

This paper investigates the differentially private problem of the average consensus for a class of discrete-time multi-agent network systems(MANSs). Based on the MANSs,a new distributed differentially private consensus algorithm(DPCA) is developed. To avoid continuous communication between neighboring agents, a kind of intermittent communication strategy depending on an event-triggered function is established in our DPCA. Based on our algorithm, we carry out the detailed analysis including its convergence, its accuracy, its privacy and the trade-off between the accuracy and the privacy level, respectively. It is found that our algorithm preserves the privacy of initial states of all agents in the whole process of consensus computation. The trade-off motivates us to find the best achievable accuracy of our algorithm under the free parameters and the fixed privacy level. Finally, numerical experiment results testify the validity of our theoretical analysis.

关键词： Average consensus differentially private event-triggered communication multi-agent network systems (MANSs)

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Random Fourier Features Based Kernel Risk Sensitive Loss Algorithm with Adaptive Moment Estimation Optimization Technology 22

Random Fourier Features Based Kernel Risk Sensitive Loss Alg...

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6th International Conference on Digital Signal processing, ICDSP 2022

作者： Wang, Daili Zheng, Yunfei Cai, Peng Liu, Qiang Shen, Minglin Wang, Shiyuan Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University China

ISBN: (纸本)9781450395809

Random Fourier features based kernel risk sensitive loss (RFFKRSL) is a popular nonlinear adaptive filtering algorithm developed in the random Fourier features space. The most attractive feature of such algorithm is that it would not cause the issue of linearly increasing network structure like the well-known kernel adaptive filtering algorithms, while having the ability to curb the negative influence induced by non-Gaussian noises. The stochastic gradient descent (SGD) method, however, is a default choice to determine the filtering coefficients of RFFKRSL, which can result in an undesirable convergence performance of the algorithm in many cases. To address this issue, two alternative optimization technologies, including adaptive moment estimation (Adam) and its extended version, i. e., Nesterov-accelerated Adam (Nadam), have been adopted to re-derive RFFKRSL. For simplicity, the proposed two algorithms are named as RFFKRSL with Adam (AdamRFFKRSL) and RFFKRSL with Nadam (NadamRFFKRSL), respectively. Although Adam and Nadam are common to deep neural network based learning methods, their applications to adaptive filtering are seldom to be seen, and the combination of them with RFFKRSL may open a new way to design nonlinear adaptive filtering algorithms that have been built with SGD method. Simulations on two time series prediction tasks are reported to demonstrate the desirable performance of the proposed algorithms. © 2022 ACM.

关键词： Stochastic systems

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An adaptive malicious punishment over secure distributed estimation under attacks 4

An adaptive malicious punishment over secure distributed est...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Hua, Yi Hu, Limei Chen, Feng Department of Electronic and Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

ISBN: (纸本)9781538683392

In this paper, we propose an adaptive malicious punishment DLMS algorithm to mitigate the adversarial attack. Two types of attacks are proposed in the WSNs. The adaptive threshold is designed to detect attacks. Then corresponding weight of malicious nodes can be reduced, due to the punishing factor. The simulations demonstrate that the proposed algorithm is robust to the adversarial attacks. © 2018 IEEE.

关键词： Component Detecting malicious nodes DLMS The adaptive threshold The malicious attack The punishing weight

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Row-Stochastic Matrices Based Distributed Optimization Algorithm with Uncoordinated Step-Sizes 6

Row-Stochastic Matrices Based Distributed Optimization Algor...

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6th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2019

作者： Li, Huaqing Wang, Jinmeng Wang, Zheng Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9781728158570

This paper investigates the distributed optimization problem over multi-agent networks, in which the target of agents is to collaboratively optimize the sum of all local objective functions. Each local objective function is uniquely known by a single agent. We concentrate on the scenario where communication among agents is portrayed as directed graphs. Based on the exact first order method, a fully distributed optimization algorithm is proposed to deal with the optimization problem. The proposed algorithm utilizes row-stochastic matrices and uncoordinated step-sizes, which exactly drives all agents to converge to the global optimization solution. Under the assumptions that the global objective function is strong convex and the local objective functions have Lipschitz continuous gradient, we show that the proposed algorithm linearly converges to the global optimization solution as long as the maximum step-size of agents does not exceed an explicitly characterized upper bound. Finally, numerical experiments are presented to demonstrate the correctness of theoretical analysis. © 2019 IEEE.

关键词： Directed graphs

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Stability of Inertial Delayed Neural Networks Via Event-Triggered Impulsive Control

Stability of Inertial Delayed Neural Networks Via Event-Trig...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Hong, Nan Zhang, Wei Zhang, Tianguang Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Department of Electronics and Information Engineering Chongqing China

ISBN: (纸本)9781665412872

This paper studies the stability of inertial delayed neural networks via event-triggered impulsive control (ETIC), where impulsive instants are determined by an effective Lyapunov-based impulsive event triggered mechanism (IETM). Based on the IETM, the Zeno behavior is excluded and ensures the globally exponential stability and h-stability of the neural networks by constructing Lyapunov function and some different restrictive conditions. In addition, the delay term in inertial neural networks is well dealt with the two lemmas given in this paper. It is shown that inertial delayed neural networks can be stabilized through this event-triggered impulsive control. Finally, two numerical examples and their simulations are carried out to verify the effectiveness of this method. © 2021 IEEE.

关键词： Time delay

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