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Electronic Materials and information Engineering (EMIE), International Conference on

作者： Longlong Zhang Maoqiu Pu Peizhi Yang Zhiyuan Zhu Key Laboratory of Advanced Technique & Preparation for Renewable Energy Materials Ministry of Education Yunnan Normal University Kunming China Guangxi key laboratory of Automobile Components and Vehicle technology Guangxi University of Science and Technology Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

ISBN: (数字)9798350390223

ISBN: (纸本)9798350390230

To fully utilize limited energy resources and address the inefficiencies in existing energy management, the authors proposed a comprehensive energy monitoring system design based on cloud computing, starting from the perspective of system network architecture. This system leverages existing resources effectively and incorporates overall scheduling, real-time monitoring, and predictive functionalities. The system operates on a cloud computing platform, processing data from three types of energy metering devices generated by sensors (electricity meter, water meter, gas meter) to provide users with real-time energy consumption data, represented as (0.50, 0.23, 0.10). These values are very close to the actual power consumption values (0.47, 0.21, 0.08), within an acceptable energy consumption range, achieving an average accuracy of 98%. This proves the high accuracy of cloud computing in remote real-time data transmission. Furthermore, the system utilizes the high reliability and scalability of cloud computing to offer integrated resource management, customized application, and virtualization platform switching services to customers, enabling information-based management of energy reserves, consumption, and equipment operation.

关键词： Meters Cloud computing Energy consumption Accuracy Switches Real-time systems Virtualization

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Consensus of multi-agent systems with dynamic join characteristics under impulsive control

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Frontiers of information Technology & Electronic Engineering 2021年第1期22卷 120-133页

作者： Xiang HU Zufan ZHANG Chuandong LI School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China

We study how to achieve the state consensus of a whole multi-agent system after adding some new agent groups dynamically in the original multi-agent *** analyze the feasibility of dynamically adding agent groups under differen t forms of net work topologies that are currently common,and obtain four feasible schemes in theory,including one scheme that is the best in actual industrial ***,we carry out dynamic modeling of multi-agent systems for the best *** control theory and Lyapunov stability theory are used to analyze the conditions so that the whole multi-agent system with dynamic join characteristics can achieve state ***,we provide a numerical example to verify the practicality and validity of the theory.

关键词： Multi-agent system Network topology Impulsive input Dynamic join charac teristics State consensus

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Sparsity-constrained Graph nonnegative Matrix Factorization for Clustering 11

Sparsity-constrained Graph Nonnegative Matrix Factorization ...

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11th International Conference on intelligent Control and information processing, ICICIP 2021

作者： Chen, keyi Che, Hangjun Yang, Xuanhao Leung, Man-Fai Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Hong Kong Metropolitan University School of Science and Technology Hong Kong

ISBN: (纸本)9781665425155

Graph nonnegative matrix factorization (GNMF) is superior for mining the intrinsic geometric structure embedded in high-dimensional data. As the sparsity of the factorized matrices is crucial for clustering, the l0 norm is commonly used in the formulated optimization problem to enforce the sparseness which makes the problem NP-hard and discontinuous. In this paper, the sparse graph nonnegative matrix factorization (SGNMF) is formulated as a global optimization problem by using the sum of inverted Gaussian functions to approximate the l0 norm, the multiplicative update rules are developed to solve the problem with guaranteed convergence. The superior performance of the proposed approach is substantiated by clustering tests on four public datasets. © 2021 IEEE.

关键词： Global optimization

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Latent multi-view subspace clustering based on Laplacian regularized representation

Latent multi-view subspace clustering based on Laplacian reg...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Wei Guo Hangjun Che Man-Fai Leung Nankun Mu Xiangguang Dai Yuming Feng School of Electronic and Information Engineering Southwest University Chongqing China School of Electronic Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China School of Computing and Information Science Faculty of Science and Engineering Anglia Ruskin University Cambridge UK Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing China

We propose a latent multi-view subspace clustering model based on Laplacian regularized representation. To emphasize the information of the representation matrix at the local level and reflect the grouping effect of clustering, a Laplacian regularization is imposed on the representation matrix. Additionally, To boost the efficiency o f c lustering, we apply nonnegative constraints on the representation matrix. A unified framework is designed to solve the proposed model by using ALM and LADMAP methods. The proposed model has excellent performance, as demonstrated by a number of experimental findings.

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Metaheuristics for Index-Tracking with Cardinality Constraints 11

Metaheuristics for Index-Tracking with Cardinality Constrain...

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11th International Conference on information Science and Technology, ICIST 2021

作者： Yuen, Man-Chung Ng, Sin-Chun Leung, Man-Fai Che, Hangjun Open University of Hong Kong School of Science and Technology Hong Kong Hong Kong Southwest University College of Electronic and Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (纸本)9781665412667

As one of the passive investment strategies, index-tracking aims to replicate market indexes to reproduce market performance. It is widely used for long-term investment. Full replication and partial index-tracking are common approaches for index-tracking problems. Although full replication tracks the chosen market index perfectly, the transaction cost is relatively high in practice. Therefore, partial index-tracking is desired that can reduce the transaction cost and avoid illiquid assets. The partial index-tracking approach selects the subset of a benchmark index and applies restrictions for the numbers of stocks with cardinality constraints. The constrained problem is converted into an unconstrained problem by adding the penalty term. This paper is concerned with the sparse index-tracking problem with cardinality constraints by various metaheuristics. Various metaheuristics are used to deal with the sparse index-tracking problem, and their performances are compared. Also, various penalty values are adopted to test the performance of the compared algorithm. © 2021 IEEE.

关键词： Constrained optimization

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Multimodal Associative Memory Based on Forgetting Memristor Bridge Synapse Circuit

SSRN

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SSRN 2023年

作者： Li, Ke Chen, Ling Li, Chuandong Qiu, Haoyang Liu, Chenchen Electronic Information and Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University 400715 China University of Maryland Baltimore County Computer Science and Electrical Engineering Department United States

Memristor is frequently used to construct synapses and memristor bridge synapse is a typical example of such a synapse. Unlike the traditional memristor bridge synapse, the forgetting memristor bridge synapse can express positive and negative weights, as well as dual weights for long-term and short-term memory. In this study, we constructed the forgetting memristor bridge synapse using the forgetting memristor SPICE model, and then simulated 1*1, 1*3, and 3*3 forgetting memristor bridge synapse networkswith neurons. We demonstrated the circuit and network’s functionality and effectiveness through simulation results and noise ***, we built the bipolar and gray-level BAM (BGBAM) network based on the forgetting memristor bridge. Owing to its dual weight characteristic, the BGBAM associative memory network uses time division multiplexing mode on the same architecture, which enables the realization of multi-modal associative memories between text, images, and audio. © 2023, The Authors. All rights reserved.

关键词： Memristors

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TSW-FD: A novel temporal and spatial domain weight analysis of feature difference for micro-expression spotting

TSW-FD: A novel temporal and spatial domain weight analysis ...

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2020 International Symposium on Automation, information and Computing, ISAIC 2020

作者： Zhang, Zhihao Mo, Fan Zhao, Ke Chen, Tong Fu, Xiaolan State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences Beijing100101 China Department of Psychology University of Chinese Academy of Sciences Beijing100049 China Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Southwest University Chongqing400715 China Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology Chongqing400715 China

The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from the original feature difference (FD) analysis, in this paper, we proposed a novel temporal and spatial domain weight analysis of feature difference (TSW-FD) to achieve micro-expression spotting. The experimental results showed that TSW-FD improved 17.86% and 24.21% in F1-Score comparing to the FD in CASME Ⅱ and SMIC-E-HS. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Finite difference method

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Memristor-based hyper-chaotic circuit for image encryption

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Chinese Physics B 2020年第11期29卷 259-270页

作者： Jiao-Jiao Chen Deng-Wei Yan Shu-Kai Duan Li-Dan Wang College of Electronic and Information Engineering Southwest UniversityChongqing 400715China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest UniversityChongqing 400715China Intelligent Transmission and Control Technology Joint Engineering Laboratory Chongqing 400715China Brain-inspired Computing and Intelligent Control Chongqing Key Laboratory Chongqing 400715China Chongqing Collaborative Innovation Center for Brain Science Chongqing 400715China School of Artificial Intelligence Southwest UniversityChongqing 400715China

The memristor is a kind of non-linear element with memory function,which can be applied to chaotic systems to increase signal randomness and *** this paper,a new four-dimensional hyper-chaotic system is designed based on a flux controlled memristor model,which can generate complex chaotic *** basic dynamic theory analysis and numerical simulations of the system,such as the stability of equilibrium points,the Lyapunov exponents and dimension,Poincare maps,the power spectrum,and the waveform graph prove that it has rich dynamic ***,the circuit implementation of this system is *** consistency of simulation program with integrated circuit emphasis(SPICE)simulation and numerical analysis proves the ability to generate ***,a new image encryption scheme is designed by using the memristor-based hyper-chaotic system proposed in this *** scheme involves a total of two *** using different security analysis factors,the proposed algorithm is compared with other image encryption schemes,including correlation analysis,information entropy,*** results show that the proposed image encryption scheme has a large key space and presents a better encryption effect.

关键词： memristor SPICE simulation hyper-chaotic system image encryption

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A distributed stochastic optimization algorithm with gradient-tracking and distributed heavy-ball acceleration

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Frontiers of information Technology & Electronic Engineering 2021年第11期22卷 1463-1476页

作者： Bihao SUN Jinhui HU Dawen XIA Huaqing LI Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information EngineeringSouthwest UniversityChongqing400715China College of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang550025China

Distributed optimization has been well developed in recent years due to its wide applications in machine learning and signal *** this paper,we focus on investigating distributed optimization to minimize a global *** objective is a sum of smooth and strongly convex local cost functions which are distributed over an undirected network of n *** contrast to existing works,we apply a distributed heavy-ball term to improve the convergence performance of the proposed *** accelerate the convergence of existing distributed stochastic first-order gradient methods,a momentum term is combined with a gradient-tracking *** is shown that the proposed algorithm has better acceleration ability than GT-SAGA without increasing the *** experiments on real-world datasets verify the effectiveness and correctness of the proposed algorithm.

关键词： Distributed optimization High-performance algorithm Multi-agent system Machine-learning problem Stochastic gradient

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Dynamics-Based Algorithm-Level Privacy Preservation for Push-Sum Average Consensus

arXiv

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arXiv 2023年

作者： Cheng, Huqiang Xie, Mengying Yang, Xiaowei Lü, Qingguo Li, Huaqing Key Laboratory of Dependable Services Computing in Cyber Physical Society-Ministry of Education College of Computer Science Chongqing University Chongqing401331 China School of Software Engineering South China University of Technology Guangzhou510006 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China

In the intricate dance of multi-agent systems, achieving average consensus is not just vital–it is the backbone of their functionality. In conventional average consensus algorithms, all agents reach an agreement by individual calculations and sharing information with their respective neighbors. Nevertheless, the information interactions that occur in the communication network may make sensitive information be revealed. In this paper, we develop a new privacy-preserving average consensus method on unbalanced directed networks. Specifically, we ensure privacy preservation by carefully embedding randomness in mixing weights to confuse communications and introducing an extra auxiliary parameter to mask the state-updated rule in initial several iterations. In parallel, we exploit the intrinsic robustness of consensus dynamics to guarantee that the average consensus is precisely achieved. Theoretical results demonstrate that the designed algorithms can converge linearly to the exact average consensus value and can guarantee privacy preservation of agents against both honest-but-curious and eavesdropping attacks. © 2023, CC BY.

关键词： Consensus algorithm

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