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

共 185 条记录，以下是81-90 订阅

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Movie preference prediction based on EEG signal under high brain correlation 4

Movie preference prediction based on EEG signal under high b...

引用

4th International Conference on Signal processing and Computer Science, SPCS 2023

作者： Yue, Yuanhao Zhao, Xingcong Zhou, Wei Liu, Guangyuan School of Electronic and Information Engineering Southwest University Tiansheng Road Beibei Chongqing400715 China Institute of Affective Computing and Information Processing Southwest University Tiansheng Road Beibei Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Tiansheng Road Beibei Chongqing400715 China

ISBN: (纸本)9781510672505

In this study, we recorded the electroencephalography (EEG) of human subjects when they watched a movie trailer. Based on the willingness preference from the subjects after finished the movie trailer watching, the EEG signals were analyzed to build regression models to predict the subjects' movie preferences. We proposed a new approach to rise the prediction accuracy. Specifically, the correlated component analysis (CCA) algorithm was used to calculate the inter-subject correlation (ISC) of each time segment in the movie trailer and the ISC of each channel in the EEG. These two states were selected to locate the moment when a specific area of the brain responds most strongly to the video stimulation, as an effective indicator for predicting individual movie preferences. The experimental results show that the method of selecting effective EEG signals at the level of ISC has achieved a better prediction effect on the GBDT regression model (R2 = 0.733, RMSE = 0.681). We also found that low-frequency EEG signals in the θ and δ bands of the parietal and occipital sites are more effective in predicting movie preferences than high-frequency EEG signals. © 2023 SPIE.

关键词： Electroencephalography

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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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An ECG Monitoring System Based on Android

An ECG Monitoring System Based on Android

引用

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

作者： Ruiqi Zhang Zhengchun Hua Chen Chen Guangyuan Liu Wanhui Wen School of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing China

ISBN: (数字)9781728165172

ISBN: (纸本)9781728165189

This study aims to design a real-time electrocardiogram (ECG) and heart rate monitoring system based on Android. The system connects Android device and a Shimmer3 ECG module, which is a wearable ECG device collecting ECG data with five electrodes. The ECG signal is amplified and filtered by internal circuit processing in Shimmer3 ECG module, and the ECG data is transmitted to an Android phone via Bluetooth. The baseline drift in ECG signal is removed through wavelet decomposition and reconstruction. Then, the processed ECG data are used to find the R wave peaks by an algorithm for automatic R peak locating and RR interval calculation. RR interval waveform is plotted and displayed on an Android phone in real time. Finally, ECG and RR intervals are saved for data playback and subsequent analysis.

关键词： Electrocardiography Bluetooth Real-time systems Smart phones Monitoring Heart rate

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

Row-Stochastic Matrices Based Distributed Optimization Algor...

引用

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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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...

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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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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...

引用

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

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

引用

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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Facial Expression Recognition of Public Speaking Anxiety

Facial Expression Recognition of Public Speaking Anxiety

引用

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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