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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Pang, Jing Su, Ye Xie, Yiyuan College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing Chongqing400715 China

ISBN: (纸本)9798350353594

Integrated photonic neural networks (IPNNs), with their ability to process large-scale data and parallelize multiple computational tasks, have shown impressive promise for applications in the field of artificial intelligence. However, due to some hard-to-ignore non-ideal characteristics of the underlying silicon photonic MZI devices constituting the IPNN, these non-ideal characteristics can cause the input signal to be affected by crosstalk noise and optical loss during transmission, thus affecting the training and inference accuracy of the IPNN. In order to solve these problems, this paper establishes an analytical model of IPNN affected by crosstalk noise and loss during the training process, covering component level, layer level and system level. Simulations using this model show that the inference accuracy of IPNN decreases by about 65% when the crosstalk noise in the training phase of IPNN reaches -20 dB, while the inference accuracy of IPNN decreases by about 55% when the optical loss reaches -0.5 dB. © 2024 IEEE.

关键词： Crosstalk

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High Contrast Ratio 4-to-2 Plasmonic Encoder Utilizing Cascaded Ring Resonators 6

High Contrast Ratio 4-to-2 Plasmonic Encoder Utilizing Casca...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Chen, Yan Xie, Yiyuan Chai, Junxiong Ye, Yichen College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing Chongqing400715 China

ISBN: (纸本)9798350353594

In this paper, a novel plasmonic 4-to-2 encoder comprising cascaded ring resonators coated with graphene layers and two metal-insulator-metal (MIM) waveguides. The encoding function operates at 850 nm by modulating the intensity of pump beam focused on the graphene layer to manipulate the state of the plasmonic resonators. The performance of the encoder is analyzed utilizing the finite-difference time-domain method, demonstrating a high contrast ratio of 15.1 dB. Thus, this efficient 4-to-2 optical encoder is well-suited for integration into optical integrated computing devices. © 2024 IEEE.

关键词： Semiconductor insulator boundaries

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A recurrent neural network for optimal energy management considering the battery cycle-life in smart grid 6

A recurrent neural network for optimal energy management con...

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

作者： Sun, Miao He, Xing School of Microelectronics Fudan University Shanghai200433 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronics and Information Engineering Southwest University Chongqing400715 China

ISBN: (纸本)9781728158570

This paper proposes a combined battery energy management (CBEM) model against the background of smart grid, which focus on the absorptive ability of Battery Energy Storage System (BESS) distinguishing to the traditional energy management. To solve the CBEM model, an one-layer recurrent neural network (RNN) is recommended. Furthermore, by considering the peak and valley periods division prices, the generators absorption and the distribution network bought from power grid are optimized. Meanwhile, the emission cost is considered in total cost and there is a corresponding constraint to control the emission and the outputs of generators. Finally, the effectiveness of the CBEM model is verified on Matlab. With the fluctuation of electrical price, the charge model and discharge model of BESS are showed. Results indicate that this model performs well in cutting the load in peak time and storage energy in valley time. © 2019 IEEE.

关键词： Recurrent neural networks

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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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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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Model-Free Reinforcement Learning Economic Dispatch Algorithms for Price-Based Residential Demand Response Management System

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 123-135页

作者： Li, Jun Li, Huaqing Huang, Tingwen Zheng, Lifeng Ji, Lianghao Yin, Shen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Mechanical and Industrial Engineering Faculty of Engineering Norwegian University of Science and Technology Trondheim7033 Norway

It is projected that plug-in electric vehicles (PEVs) would steadily increase as household appliances. However, PEVs’ high power consumption, stochastic usage patterns, and storage capacity will surely result in a rise in the elasticity of demand response and pose significant difficulties for price-based residential demand response management (PRDRM). This artcle aims to optimize a two-tier globally shared nonconvex PRDRM problem with local constraints and PEVs, known as social welfare: maximizing retailer profits and minimizing the combined residential costs. This is done by balancing residential electricity use with retail electricity prices in an unknown market environment. The proposed online/offline model-free reinforcement learning-based economic dispatch (MFRL-ED) methods can adaptively decide on the ideal retail price sequence by integrating the daily residential-retailer behavior model with the agent-environment interaction method, providing a basic MFRL-ED solution for PRDRM without a system identification step and an accurate load-retail model. Experiments show that MFRL-ED methods provide an effective class of PRDRM solutions. © 2023 Institute of Electrical and Electronics Engineers. All rights reserved.

关键词： Reinforcement learning

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Observer-Based Consensus of nonlinear Multi-Agent Systems With Input Delay via Delay-Dependent Event-Triggered Control

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 157-166页

作者： Wei Zhang Bingyan Gong Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronics and Information Engineering Southwest University Chongqing China

The distributed control for leader-following consensus problem of nonlinear multi-agent systems with input delay is investigated in this paper. Based on observer state information, an improved distributed truncated prediction control strategy is proposed in order to address the issue of input delay. Furthermore, a delay-dependent event-triggered control protocol is designed to alleviate the use of computation resources and communication bandwidth. Unlike the existing event-triggered protocol, the protocol in the article is delay-dependent and specially designed for systems with input delay. Moreover, the Zeno behavior does not occur. It should be pointed out that, our observer-based control is significant for practical applications where the state of agents cannot be directly obtained. Utilizing the Lyapunov-Krasoviskii function theory, the sufficient conditions of the consensus under above two control methods are obtained. Lastly, we illustrate the feasibility of our results by illustrative examples.

关键词： Delays Protocols Observers Multi-agent systems Linear matrix inequalities Sufficient conditions Cyber-physical systems

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A simple motion deblurring method by two continuous images

A simple motion deblurring method by two continuous images

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

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

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

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.

关键词： motion blur continuous frame image deblurring PSF SIFT motion blur deblurring Point spread function Sifting SHARPNESS OF IMAGE images Continuous structures continuous image

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Personality recognition based on ECG in response to VR emotional stimuli 23

Personality recognition based on ECG in response to VR emoti...

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3rd International Conference on Bioinformatics and intelligent Computing, BIC 2023

作者： Lan, Ping Xie, Jialan Hu, Zhaonian Liu, Guangyuan College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China Institute of Affective Computing and Information Processing Southwest University Chongqing400715 China Key Laboratory of Cognition and Personality Ministry of Education Faculty of Psychology Southwest University Chongqing400715 China

ISBN: (纸本)9798400700200

This paper explores the feasibility and effect of using ECG signals in response to virtual reality(VR) emotional stimuli for personality recognition. Personality represents an individual''s behavior pattern, so it has extensive research significance to identify personality. In the field of personality recognition, there have been researches on the use of physiological signals to recognize personality recently, but there have been no studies on personality recognition in VR scenarios. VR technology has been applied in many fields, and in the field of emotion recognition, the advantage of VR video as emotional arousal material has been proved. We designed the emotional stimulation experiment in VR scene to collect ECG signals, and constructed the personality recognition model. The results showed that the F1 scores of neuroticism, extraversion, openness, agreeableness and conscientiousness using only ECG were 0.79, 0.80, 0.81, 0.73 and 0.81, respectively, which were much higher than the random level. And we found that in VR scenes, negative emotional stimulation can achieve better personality recognition effect. Our results confirm the feasibility of personality recognition using ECG signals in response to VR emotional stimuli. © 2023 ACM.

关键词： Electrocardiograms

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