检索结果-内蒙古大学图书馆

Neural Network-Based Adaptive Containment Control Algorithms Design for nonlinear Multiagent Systems with Switching Topologies

引用

COGNITIVE COMPUTATION 2023年第1期15卷 90-102页

作者： Huang, Jie Wang, Xin Xu, Rui Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400044 Peoples R China

This paper discusses the containment control problem of nonlinear multiagent systems with unknown disturbance and switching topology. The novel model of nonlinear multiagent systems is given and the dynamic functions of this model are considered to be continuous. Utilizing the approximation capability of the neural networks to estimate the unknown external disturbance and unknown nonlinear functions in the dynamic functions of nonlinear multiagent systems, which designs disturbance observer and containment controller. The containment control problem can be addressed with the proposed algorithm, applying the Lyapunov functions, graph theory, and inequality techniques. The nonlinear multiagent systems are cooperatively semi-globally uniformly ultimately bounded and at the end of this paper, a simulation example is given to illustrate the effectiveness of the approach proposed.

关键词： Neural network Multiagent systems Switching topologies Adaptive containment control

来源：评论

学校读者我要写书评

暂无评论

Asynchronous Distributed Nonsmooth Composite Optimization via Computation-Efficient Primal-Dual Proximal Algorithms

引用

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2024年第2期9卷 1595-1609页

作者： Ran, Liang Li, Huaqing Zheng, Lifeng Li, Jun Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

This paper focuses on a distributed nonsmooth composite optimization problem over a multiagent networked system, in which each agent is equipped with a local Lipschitz-differentiable function and two possibly nonsmooth functions, one of which incorporates a linear mapping. To address this problem, we introduce a synchronous distributed algorithm featuring uncoordinated relaxed factors. It serves as a generalized relaxed version of the recent method TriPD-Dist. Notably, the considered problem in the presence of asynchrony and delays remains relatively unexplored. In response, a new asynchronous distributed primal-dual proximal algorithm is first proposed, rooted in a comprehensive asynchronous model. It is operated under the assumption that agents utilize possibly outdated information from their neighbors, while considering arbitrary, time-varying, yet bounded delays. With some special adjustments, new asynchronous distributed extensions of existing centralized methods are obtained via the proposed asynchronous algorithm. Theoretically, a new convergence analysis technique of the proposed algorithms is provided. Specifically, a sublinear convergence rate is explicitly derived by showcasing that the iteration behaves as a nonexpansive operator. In addition, the proposed asynchronous algorithm converges the optimal solution in expectation under the same step-size conditions as its synchronous counterpart. Finally, numerical studies substantiate the efficacy of the proposed algorithms and validate their performance in practical scenarios.

关键词： Delays Optimization Distributed algorithms Convergence Vectors Convex functions Computational intelligence Asynchrony delayed communication nonsmooth convex functions distributed optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Mean square exponential stabilization analysis of stochastic neural networks with saturated impulsive input

引用

NEURAL NETWORKS 2024年 170卷 127-135页

作者： Deng, Hao Li, Chuandong Chang, Fei Wang, Yinuo Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

The exponential stabilization of stochastic neural networks in mean square sense with saturated impulsive input is investigated in this paper. Firstly, the saturated term is handled by polyhedral representation method. When the impulsive sequence is determined by average impulsive interval, impulsive density and mode-dependent impulsive density, the sufficient conditions for stability are proposed, respectively. Then, the ellipsoid and the polyhedron are used to estimate the attractive domain, respectively. By transforming the estimation of the attractive domain into a convex optimization problem, a relatively optimum domain of attraction is obtained. Finally, a three-dimensional continuous time Hopfield neural network example is provided to illustrate the effectiveness and rationality of our proposed theoretical results.

关键词： Saturated impulsive input Stochastic neural networks Average impulsive interval Impulsive density Attractive domain

来源：评论

学校读者我要写书评

暂无评论

Nonconvex low-rank tensor approximation with graph and consistent regularizations for multi-view subspace learning

引用

NEURAL NETWORKS 2023年第1期161卷 638-658页

作者： Pan, Baicheng Li, Chuandong Che, Hangjun Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

Multi-view clustering is widely used to improve clustering performance. Recently, the subspace clustering tensor learning method based on Markov chain is a crucial branch of multi-view clus-tering. Tensor learning is commonly used to apply tensor low-rank approximation to represent the relationships between data samples. However, most of the current tensor learning methods have the following shortcomings: the information of the local graph is not taken into account, the relationships between different views are not shown, and the existing tensor low-rank representation takes a biased tensor rank function for estimation. Therefore, a nonconvex low-rank tensor approximation with graph and consistent regularizations (NLRTGC) model is proposed for multi-view subspace learning. NLRTGC retains the local manifold information through graph regularization, and adopts a consistent regularization between multi-views to keep the diagonal block structure of representation matrices. Furthermore, a nonnegative nonconvex low-rank tensor kernel function is used to replace the existing classical tensor nuclear norm via tensor-singular value decomposition (t-SVD), so as to reduce the deviation from rank. Then, an alternating direction method of multipliers (ADMM) which makes the objective function monotonically non-increasing is proposed to solve NLRTGC. Finally, the effectiveness and superiority of the NLRTGC are shown through abundant comparative experiments with various state-of-the-art algorithms on noisy datasets and real world datasets.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Multi -view clustering Subspace clustering Spectral clustering Nonconvex low -rank tensor approximation

来源：评论

学校读者我要写书评

暂无评论

Neural-Network-Based Adaptive Consensus Control for nonlinear Multiagent Systems Subject to Time Delays and Unknown Disturbance

引用

NEURAL PROCESSING LETTERS 2023年第9期55卷 11885-11904页

作者： Wen, Ruolan Wang, Xin Xu, Rui Pang, Ning Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400044 Peoples R China

The current investigation aims at the adaptive consensus issue for a class of nonlinear multiagent systems with time delays and unknown disturbances under a directed graph topology. A novel designed disturbance observer eliminates the impact on the consensus induced by unknown external disturbances. Furthermore, the Lyapunov-Krasovskii functional method is applied to tackle the time delays in the design process. With the approximation capability of neural networks, the adaptive controller is developed by the backstepping technique, which can alleviate the burden of computing and make the consensus tracking error converge to a small compact region. The control scheme proposed in this paper enables the nonlinear multiagent systems to achieve consensus output. Meanwhile, a numerical simulation example is performed to verify the effectiveness of the proposed scheme.

关键词： nonlinear multiagent systems Consensus issue Neural network Disturbance obsever Time delays

来源：评论

学校读者我要写书评

暂无评论

Observer-Based Event-Triggered Adaptive Control for nonlinear Multiagent Systems With Unknown States and Disturbances

引用

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第9期34卷 6663-6669页

作者： Pang, Ning Wang, Xin Wang, Ziming Southwest Univ Coll Westa Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Guangdong Prov Key Lab Intelligent Decis & Coopera Guangzhou 510006 Peoples R China

Based on radial basis function neural networks (RBF NNs) and backstepping techniques, this brief considers the consensus tracking problem for nonlinear semi-strict-feedback multiagent systems with unknown states and disturbances. The adaptive event-triggered control scheme is introduced to decrease the update times of the controller so as to save the limited communication resources. To detect the unknown state, external disturbance, and reduce calculation workload, the state observer and disturbance observer as well as the first-order filter are first jointly constructed. It is shown that all the output signals of followers can uniformly track the reference signal of the leader and all the error signals are uniformly bounded. A simulation example is carried out to further prove the effectiveness of the proposed control scheme.

关键词： Event-triggered control multiagent system observer tracking control

来源：评论

学校读者我要写书评

暂无评论

Arbitrary-Time Stable Gradient Flows Using Neurodynamic System for Continuous-Time Optimization

引用

IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2023年第12期70卷 4559-4563页

作者： Wen, Hongsong He, Xing Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this brief, two arbitrary-time stable gradient flows are proposed to solve the continuous-time optimization problems based on nonlinear neurodynamic system. In contrast to the conventional gradient flow methods, the proposed gradient flows adopt the arbitrary-time sliding mode controller. It is shown that the proposed gradient flows converge to the solution of the optimization problem in arbitrary time under certain mild conditions. Finally, a numerical example is given to verify the main results. In addition, the effectiveness of the proposed gradient flows is further verified by FPGA hardware implementation.

关键词： Arbitrary-time stable sliding mode gradient flow FPGA hardware implementation

来源：评论

学校读者我要写书评

暂无评论

Dynamic Resistance Loading Technology-Based Metasurface Design With Co-Regulated Band-Notch Frequency of Radiation

引用

IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2025年

作者： Li, Pan Feng, Yunfei Qu, Meijun Su, Jianxun Yang, Lixia Nayyeri, Vahid Anhui Univ Informat Mat & Intelligent Sensing Lab Anhui Prov Hefei 230601 Peoples R China Commun Univ China State Key Lab Media Convergence & Commun Beijing 100024 Peoples R China Beijing Univ Posts & Telecommun Sch Integrated Circuits Beijing 100876 Peoples R China Iran Univ Sci & Technol Sch Adv Technol Tehran *** Iran

For electromagnetic stealth against radar digital signal processing systems, real-time adjustable impedance of the platform is urgently needed under the guaranteed instantaneous tracking capability. In this study, a multifunctional metasurface (MMS) based on dynamic resistance loading (DRL) technology is proposed to dynamically modulate the scattering amplitude of a band-notch adjustable radiation array. Based on the theoretical analysis of the cooperation mechanism between the switchable band-notch and DRL frameworks, the lossy and lossless layers are separately designed to construct the MMS. A dual-linear polarized DRL absorber is generated by continuously transforming the forward voltage of the orthogonal p-i-n diodes on the lossy layer. Meanwhile, the reverse voltage changing of the varactor diode on the lossless layer results in an adjustable band-notch effect. After joint optimization between the 3-D dipole element and the MMS, an 8 x 4 radiation-stealth metasurface (RSMS) is then fabricated and measured. With the changing voltage of p-i-n diodes, the wideband radar cross section (RCS) amplitude regulation of dual-linear polarization has been proven to be greater than 15 dB. For a specific capacitance of the varactor diodes, the beam scanning angle of the RSMS is up to 45(degrees) at 4.6 GHz. The RSMS has realized instantaneous frequency switching of radiation under the premise of wideband tunable scattering control. The proposed design method provides an effective stealth scheme for digital signal processing radar system.

关键词： Absorption Impedance Radar cross-sections Metasurfaces Substrates Switches Loading Wideband Radar tracking Surface impedance Band-notch adjustable radiation array dynamic resistance loading (DRL) technology multifunctional metasurface (MMS) radiation-stealth metasurface (RSMS)

来源：评论

学校读者我要写书评

暂无评论

Multi-Leader Bipartite Consensus of Stochastic Delayed Signed Networks With Event-Triggered Unbounded Delayed Impulses

引用

IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2023年第3期70卷 1049-1053页

作者： Zhang, Wei Zhou, Zichuan Hong, Nan Southwest Univ Dept Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

Unbounded delayed impulsive controlled multi-leader delayed stochastic signed networks are investigated in this brief. A multileader model based on relays to compensate for topological differences is given. In addition, through an event-triggered mechanism, a probability-based unbounded delayed impulsive control model for bipartite consensus is proposed, which shows that as long as the impulses satisfying certain conditions of time delay are properly blocked, the system is still able to maintain convergence and the Zeno behavior is naturally excluded. Based on the above event-triggered control method, sufficient conditions for the bipartite consensus of multileader and leaderless delayed stochastic signed networks are obtained using the Lyapunov function method and Ito' formula. Finally, the validity of the obtained results is supported by two examples.

关键词： Delays Stochastic processes Delay effects Behavioral sciences Topology Lyapunov methods Couplings Multi-leader stochastic signed networks delayed impulse bipartite consensus

来源：评论

学校读者我要写书评

暂无评论

Autonomic Nervous Pattern Recognition of Students' Learning States in Real Classroom Situation

引用

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2023年第1期10卷 220-233页

作者： Chen, Shi Hu, Zhaonian Li, Shanshan Hu, Xiaorou Liu, Guangyuan Wen, Wanhui Southwest China Univ Coll Elec tron & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

The current work applied machine learning methods to analyze students' group and individual learning states in the real classroom environment. The purpose is to provide insights into the learning process for teachers and students, so that they can manage the learning process effectively. We extracted three couples of learning states in real classroom learning, i.e., information input/processing and retrieval/processing states, cognitive load matching and mismatching states, and mental fatigue and nonfatigue states. The recognition of the above three couples of learning states was regarded as five binary classification problems. We collected electrocardiogram (ECG) data from 45 college students during their classes of circuit analysis and calculated the peaks of two consecutive R waves (RR) interval series from the ECG data. For each binary classification problem, RR interval features and classifiers were compared to find the critical feature subsets and suitable classifiers for the recognition of learning states. The generalization accuracies of the machine learning models were in the range of 58.41%-82.35% on the validation sets independent of classifier training and feature selection. The results show that it is feasible to monitor students' learning states through machine learning methods.

关键词： Task analysis Fatigue Electrocardiography Electroencephalography Education Load modeling information processing Artificial intelligence plus education learning states neurophysiological response pattern recognition physiological measurement

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：