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检索条件"机构=Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing"

共 180 条记录，以下是131-140 订阅

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Accelerated Distributed Optimization over Directed Graphs with Row and Column-Stochastic Matrices

Accelerated Distributed Optimization over Directed Graphs wi...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Jinhui Hu Yifan Zhu Huaqing Li Zheng Wang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

In this paper, we study distributed optimization problem over multi-agent networks where the goal is to find the global optimal of a sum of convex functions over strongly connected and directed graphs. A novel distributed algorithm is proposed where both row and column-stochastic matrices are utilized to bypass the limits of the implementation of doubly-stochastic matrices or eigenvector estimation in related work. Besides, it has an evident expression and accelerated convergence by introducing the momentum term. Combining the Generalized Small Gain Theorem with Linear Time Invariant (LTI) system inequality, the algorithm is proved to be able to linearly converge to the exact optimal solution. Furthermore, the ranges of stepsize and momentum paramater are characterized, respectively. Finally, simulation results illustrate effectiveness of the method and correctness of theoretical analysis.

关键词： Radio frequency Convergence Optimization Acceleration Eigenvalues and eigenfunctions Convex functions Linear matrix inequalities

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Row-Stochastic Matrices Based Distributed Optimization Algorithm With Uncoordinated Step-Sizes

Row-Stochastic Matrices Based Distributed Optimization Algor...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

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

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

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.

关键词： Distributed optimization directed graphs uncoordinated step-sizes row-stochastic matrices directed graphs Objective function Optimization algorithms Agents Global optimization Dyscoordination NETWORKING AGENT Distribute matrices

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The Kernel Recursive Generalized Cauchy Kernel Loss Algorithm

The Kernel Recursive Generalized Cauchy Kernel Loss Algorith...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Wei Shi Kui Xiong Shiyuan Wang College of Electronic and Information Engineering Southwest University The Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

As a nonlinear measure similarity developed in a kernel space, the generalized correntropic loss (GC-Loss) has been successfully used for signal processing and machine learning in non-Gaussian situations thanks to its ability of extracting high-order statistical properties of data. However, a highly non-convex performance surface in GC-Loss leads to poor optimization performance. To address this issue, we propose a new similarity measure developed in the kernel space by combining a generalized Gaussian distributed kernel function into the Cauchy loss. By minimizing the proposed loss function and using the kernel method, a novel kernel recursive generalized Cauchy kernel loss (KRGCKL) algorithm in the reproducing kernel Hilbert space (RKHS) is proposed. Simulations on different examples under non-Gaussian noises show the superiorities of KRGCKL over other representative algorithms in terms of filtering accuracy and robustness to large outliers.

关键词： Generalized Cauchy kernel loss kernel method robustness non-Gaussian noise kernel method non-Gaussian noise Seeds similar measure Kernel attribute data Cauchy Robustness Recursive

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A Distributed Dynamic Resource Allocation Strategy in A Large-scale Micro-grids Group

A Distributed Dynamic Resource Allocation Strategy in A Larg...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Zao Fu Xing He Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

In this paper, a dynamic economic dispatch problem (DEDP) with renewable energy generators is studied. With the purpose of minimizing the cost of DEDP and optimally allocate the load demand among the interconnected generators considering ramp-rate limits and generation limits, an effective continuous-time distributed algorithm based on interior point methods and primal-dual methods is proposed. In order to overcome the drawbacks of the renewable energy, a parallel system composed with flywheel energy storage systems and renewable energy generators is proposed to work in a constant power output mode. In addition, the using of switched systems makes the optimal solution more accurate. The excellent performance of the proposed algorithm is verified by IEEE 30-bus system with the REG based simulation.

关键词： Dynamic economic dispatch renewable energy Continuous-time distributed algorithm Renewable energy flywheel energy storage system MICRO-GRID dynamos rate limitation Switched systems DYNAMIC ECONOMIC ANALYSIS Resource utilization management of resources

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The Effect of Long-Term Apnea on the Autonomic Nervous System

The Effect of Long-Term Apnea on the Autonomic Nervous Syste...

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International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Fanmeng Kong Wanhui Wen Guangyuan Liu Xuehong Yang Ronglong Xiong School of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Processing acceptable Chongqing China

The complexity of physiological system can be well represented by the complexity of time series. In this paper, complexity analysis was performed on the inter-beat-interval(IBI) of apnea syndrome and normal sleep population. Hurst exponent, sample entropy and fractal dimension were used as three indicators of complexity measurement. The results show that optimal combination of statistical and nonlinear features with the Support Vector Machine (SVM) can achieve the apnea recognition accuracy of up to 75.51%. In the complexity measurement, t-test shows that the average of Hurst exponent, sample entropy or fractal dimension of the normal sleep group was significantly larger than that of the apnea group. The results show that long-term apnea syndrome will cause certain damage to the autonomic nerve system.

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Cross-Subject Emotion Recognition with a Decision Tree Classifier Based on Sequential Backward Selection

Cross-Subject Emotion Recognition with a Decision Tree Class...

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International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Wenge Jiang Guangyuan Liu Xingcong Zhao Fu Yang School of Electronic and Information Engineering Southwest University Chongqing China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China

Many of the current emotion recognitions are intra-subject, the reason is that recognize cross-subject emotions have always been difficult. In this paper, we proposed a decision tree classifier based on sequential backward selection (DT-SBS), and "leave-one-subject-out" verification strategy was used for evaluating performance of cross-subject emotion recognition. Power spectral density (PSD) was extracted from EEG signals as feature set. The emotion recognition performance of the method we proposed was examined on EEG data of a group of subjects. The pictures were utilized to stimulate the emotion of 12 subjects and we collected their EEG signals (PEEG), the mean recognition accuracy of 65.8%. The dataset for emotion analysis using physiological signals (DEAP) was utilized to verify the method we proposed in this paper and the mean recognition accuracy of 65.2%. Compared with the performance reported in the existing literature, the method we proposed in this paper was effective in cross-subject emotion recognition. In addition, the emotion recognition performance of different rhythms were explored, we found that the mean recognition accuracy of PSD in the gamma rhythm achieved the best mean recognition accuracy compared with the other rhythms; the high frequency bands contained higher emotional information than the low frequency bands.

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An adaptive malicious punishment over secure distributed estimation under attacks 4

An adaptive malicious punishment over secure distributed est...

引用

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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Association Rules Hiding via Multi-Objective Differential Evolution Algorithm

Association Rules Hiding via Multi-Objective Differential Ev...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Nankun Mu Fan Yang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing P.R. China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

Association rules (ARs) mining has been widely used in discovering interesting patterns from massive data as a key data mining technique. However, this mining technique may lead to the disclosure of sensitive ARs, and thus, the ARs hiding strategy is very important and necessary. In this paper, a novel ARs hiding method (DEvoArH) is proposed for hiding the ARs. Noting that there are three side-effects in ARs hiding (ARH), i.e., the hiding failure rate, the lost rules rate, and the ghost rules rate, a multi-objective differential evolution algorithm is carefully designed. Specifically, the Pareto-optimal solutions are defined as the elite set, and then each solution is capable of learning from the elite set with a certain probability. Considering the convergence speed and search ability, a directional mutation and random mutate round is introduced into the mutation operator. Besides, to further decrease the data change rate, a database pre-processing mechanism is proposed to filter the unrelated data before the hiding process. Finally, the results of the comparison experiments also demonstrate the superiority of the proposed ARH method in terms of the three side-effects and efficiency.

关键词： association rules hiding multi-objective optimal evolutionary algorithm

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Privacy-Preserving Fuzzy Multi-keyword Search for Multiple Data Owners in Cloud Computing

Privacy-Preserving Fuzzy Multi-Keyword Search for Multiple D...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Lvhao Chen Xiaofeng Liao Nankun Mu Jiahui Wu Junqing Junqing Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Electronic and Information Engineering Southwest University Chongqing P.R. China Computer Science Chongqing University Chongqing P. R. China Le Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Electronic and Information Engineering Southwest University Chongqing P.R. China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

With cloud computing's development, more users are decide to store information on the cloud server. Owing to the cloud server's insecurity, many documents should be encrypted to avoid information leakage before being sent to the cloud. Nevertheless, it leads to the problem that plaintext search techniques can not be directly applied to the ciphertext search. In this case, many searchable encryption schemes based on single data owner model have been proposed. But, the actual situation is that users want to do research with encrypted documents originating from various data owners. This paper puts forward a privacy-preserving scheme that is based on fuzzy multi-keyword search (PPFMKS) for multiple data owners. For the sake of espousing fuzzy multi-keyword and accurate search, secure indexes on the basis of Locality-Sensitive Hashing (LSH) and Bloom Filter (BF)are established. To guarantee the search privacy under multiple data owners model, a new encryption method allowing that different data owners have diverse keys to encrypt files is proposed. This method also solves the high cost caused by inconvenience of key management.

关键词： Cloud computing Servers Indexes Encryption Data privacy

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The Design of PID Controller Based on Improved Bird Swarm Algorithm 5

The Design of PID Controller Based on Improved Bird Swarm Al...

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5th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2018

作者： Qiao, Dewen Mu, Nankun Liao, Xiaofeng Wang, Huiwei Yang, Fan College of Electronic and Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China

ISBN: (纸本)9781538670880

The proportional - integral - derivative(PID)controller has been widely employed in industrial control systems. However, the PID parameters obtained by Ziegler-Nichols(Z-N)method are difficult to show superior performance. Based on the improved bird swarm algorithm(IBSA), a method of parameter optimization of PID controller is proposed in this paper. We improve the three parameters C and S respectively. The ω is the inertia coefficient added to the bird swarm algorithm(BSA). The C and S are cognitive coefficient and social coefficient of BSA respectively. In addition, the PID controller using IBSA is also called IBSA-PID controller. In order to validate the superiority of IBSA, we compare IBSA with particle swarm optimization(PSO), genetic algorithm(GA)and bird swarm algorithm(BSA)under the aid of integrated time and absolute error(ITAE). Experimental results validate that IBSA has superior performance than other algorithms on the aspect of convergence, robust, and time cost. © 2018 IEEE.

关键词： Three term control systems

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