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

共 163 条记录，以下是81-90 订阅

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A Novel Distributed Algorithm to Seek GNE for Aggregative Games via Primal-Dual Proximal Gradient

A Novel Distributed Algorithm to Seek GNE for Aggregative Ga...

引用

International Conference on Control, Automation and Robotics (ICCAR)

作者： Zhe Li Huaqing Li Liang Ran Songyang Li Lvming Fan Lifeng Zheng Jun Li Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

In this paper, the generalized Nash equilibria (GNE) problems over the aggregative game is concerned inspired by the widely application of non-cooperative game in many fields. In the game, each agent aims to minimize its own objective function that depends on both its private decision and the average decision information of all agents’. Furthermore, decision variables are within feasible decision sets and shares a global coupling inequality constraint. To seek the GNE, a novel distributed primal-dual proximal algorithm is proposed. Meanwhile, the proposed algorithm adopts edge-based communication model and takes uncoordinated step-sizes that avoid the conservativeness. By the theories of monotone inclusion and averaged operators, convergence of the algorithm is proved. Finally, numerical studies on electric vehicles path and destination strategy problem are conducted to clarify the efficiency of the proposed algorithm.

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Robust Multi-kernel Generalized Maximum Correntropy Filters

Robust Multi-kernel Generalized Maximum Correntropy Filters

引用

IEEE International Conference on Electronic information and Communication Technology (ICEICT)

作者： Qiaona Sun Tao Zhang Xuewei Huang Shiyuan Wang College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (数字)9781728190457

ISBN: (纸本)9781728190464

The traditional multi-kernel filtering algorithms are proposed by combining multiple kernel with the second similarity measure. Nevertheless, these multi-kernel filters suffer from both heavy computation burden and divergence for impulsive noise environments. To deal with these challenges for online applications, the multi-kernel generalized maximum correntropy (MKGMC) algorithm is developed for improving both precision and stability under the generalized maximum correntropy criterion. To alleviate the complex network structure of MKGMC, using the vector quantization strategy in MKGMC develops quantized MKGMC (QMKGMC) to reduce the computational and spatial complexity. From the viewpoints of precision and stability, the proposed algorithms outperform other typical compared algorithms on time series prediction.

关键词： Vector quantization Stability criteria Time series analysis Filtering algorithms Predictive models Prediction algorithms Robustness

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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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Recognition of Social Anxiety through the Analysis of BVP Volume Series

Recognition of Social Anxiety through the Analysis of BVP Vo...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Guohong Zheng Guangyuan Liu Hui Hu Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9781509035595

Social anxiety (SA) is highly prevalent in the general population, usually causing the impairment of social function and bringing mental and physical tortures to people. Accurate recognition of SA is significant to help people alleviate their anxiety through appropriate ways of emotion regulation. This paper presents the blood volume pulse (BVP) volume series for the recognition of SA. 30 subjects' high anxiety state and low anxiety state are respectively induced by impromptu speaking with 21 audience and without audience. The mean and the weighted Krawtchouk moments are extracted as the features. Two sample t-test shows that the higher degree of anxiety, the smaller mean of the BVP volume series. Support vector machines and leave-one-subject-out cross validation are used for the recognition of SA. The result shows that the recognition accuracy of high anxiety state and low anxiety state are 90% and 86.67%, respectively.

关键词： Physiology Public speaking Feature extraction Emotion recognition Support vector machines Sociology Statistics

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Facial Expression Recognition of Public Speaking Anxiety

Facial Expression Recognition of Public Speaking Anxiety

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International Symposium on Computational Intelligence and Design, ISCID

作者： Fuli Huang Wanhui Wen Guangyuan Liu Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9781509035595

Public Speaking Anxiety (PSA) is one of the most universal subtypes of social anxiety, and the facial expression recognition of PSA is an immediate area of research focus. The experiment obtained the facial expression data of 18 postgraduates in their thesis defense for the master's degree. Then, valid data were selected by using self-evaluation of the subject and the average evaluation of 5 audience. Next, the paper used Active Shape Model (ASM) algorithm for feature extraction of 68 feature points in 5 facial zones. Moreover, the paper applied support vector machine algorithm to recognize the social anxiety state according to the displacements of the feature points, and backward selection (BS) algorithm was used to find out the most important features in recognition. The result illustrated the validity of the method and obtained the best correct rate of 99% in the recognition of social anxiety state. Meanwhile, the maximum displacement zone in social anxiety state is jaw, and followed by mouth, eyebrow, eyes and nose. Obvious individual differences were found in the formation of anxious facial expression.

关键词： Mouth Feature extraction Public speaking Face Speech Nose Face recognition

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Evolution of Facial Tissue Oxygen Saturation and Detection of Human Physical Stress

Evolution of Facial Tissue Oxygen Saturation and Detection o...

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Image processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Xinyu Liu Xiao Xiao Ranlei Cao Tong Chen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

Physical stress has a direct impact on human health, which makes the detection of physical stress necessary in daily life. In this paper, we extracted tissue oxygen saturation (StO2) by hyperspectral imaging to detect and distinguish physical stress from relaxation state remotely. During the physical stress experiment, we observed that the facial StO2 right after the stress can be either increased and decreased comparing to the baseline, the StO2 after two minutes recovered towards the baseline. This changes of StO2 is reported for the first time. Based on the findings, we also located some useful ROIs on face for the detection of human physical stress.

关键词： physical stress stress detection tissue oxygen saturation hyperspectral imaging physical stress hyperspectral imagery human health Oximetry Face

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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 hybrid intelligent system for assisting low-vision people with over-the-counter medication 12

A hybrid intelligent system for assisting low-vision people ...

引用

12th International Conference on information Science and Technology, ICIST 2022

作者： Leung, Man-Fai Che, Hangjun Kwok, Chin-Hung Chan, Lewis Faculty of Science and Engineering Anglia Ruskin University Cambridge United Kingdom College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China School of Science and Technology Hong Kong Metropolitan University Hong Kong Hong Kong

ISBN: (数字)9781665485821

ISBN: (纸本)9781665485821

Because people with low vision have difficulty pur-chasing and taking the correct medicine and dosages on time, this paper presents a system with a Flask Server and Android application that assists low-vision people with using over-the-counter (OTC) medication correctly. The system is mainly divided into three parts: an Android application, a Flask server and a MongoDB database. The application provides a medication time reminder, medicine information retrieval and image capture for recognition functions. A server recognizes the medication package by combining optical character recognition (OCR) and an image classification convolutional neural network (CNN). A database is used to store and provide medicine information. The experimental results show that the recognition performance has up to 96.1% accuracy. Moreover, the approach is shown to be able to handle out-of-distribution images. © 2022 IEEE.

关键词： Image classification

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A Novel Privacy-Preserving Data Integrity Verification by Partial Delegation

A Novel Privacy-Preserving Data Integrity Verification by Pa...

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International Conference on information Science and Technology (ICIST)

作者： Runze Ji Nankun Mu Xiaofeng Liao The Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing P.R.China

Recently, cloud storage is widely concerned due to the properties of low cost, advanced technology and efficient business model, and has been made a rapid development. However, as a new storage model, there are known security and privacy issues in migrating data to the cloud. Therefore, how to ensure the integrity and correctness of data storage is the main research direction and development of cloud storage technology. Moreover, the main purpose of the data integrity verification mechanism is to verify that the data is completely stored in the cloud server and is not modified maliciously or deleted. Sometimes the user can't perform data integrity verification for some reason, and the verification right need to be delegate to a third party auditor. In this paper, we proposed: (1) a new data integrity verification by partial delegation(PDIPD) is proposed, which delegates the remote data possession checking to a third party auditor. Compared with the existing data integrity verification scheme, the new scheme has less computational overhead and the flexibility at the same security level. (2) Extensive security analyses show this scheme is provable secure in random oracle. Estimating the cost of basic cryptographic and analyzing the experiment show, the proposed schemes are highly efficient and practical.

关键词： Data integrity Cloud computing Servers Data models Games Public key

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Effects of Acute Moderate Intensity Exercise on Emotion Based on beta Power in EEG 2019

Effects of Acute Moderate Intensity Exercise on Emotion Base...

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Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

作者： Pengfei Gao Zhengji Long Zhangyan Xiao Fu Yang Jihai Zhang Guangyuan Liu School of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Processing Chongqing China

ISBN: (纸本)9781450376273

According to previous studies, high anxiety leads to an increase in beta power, while pleasure and relaxation of emotion reduces beta power. In this experiment, the International Standard Picture Stimulation Library(IAPS) was used to induce positive and negative emotions of subjects, and EEG signals were collected when subjects were looking at pictures. Comparing the beta power of positive and negative EEG induced by before and after exercise, we found that the power of beta stimulated by positive and negative pictures before exercise is generally greater than that after exercise. It indicates that subjects were happier when facing positive stimuli than before exercise, and less negative emotions were produced when facing negative stimuli than before exercise. In short, acute moderate intensity exercise can improve people's negative emotion in the face of negative stimuli. The purpose of this study is to explore the mechanism of the effect of acute moderate intensity exercise on emotion by analyzing beta power in late positive potential (LPP).

关键词： moderate emotion exercise beta power

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