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

共 178 条记录，以下是41-50 订阅

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Data-driven current sharing and voltage regulation for DC microgrid with unknown voltage loss

Data-driven current sharing and voltage regulation for DC mi...

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2021 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2021

作者： Shi, Rui Wang, Aiqing Dong, Tao Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronics and Information Engineering Southwest University Chongqing400715 China

ISBN: (纸本)9781665443227

Current sharing and voltage regulation are two basic issues in DC microgrid. Most of the existing studies about current sharing and voltage regulation are based on the ideal case that there is no voltage loss on power line. However, in practical DC microgrid, many unknown factors may lead to voltage loss on power line, which make the present algorithms are unavailable in practical application. To solve the problem, in this paper, a novel model of current sharing and voltage regulation is proposed by using an unknown nonlinear function to describe the voltage loss on power line. Then, a novel control scheme is proposed based on pre-compensation technology, which can circumvent the unknown voltage loss. The control scheme is consisted of three parts: critic network, compensator and controller. The iterative performance is computed by critic network. The compensator is used to constitute the compensator parameter according to the iterative performance. The controller is used to generate control input by using compensator parameter. Finally, an example is given to demonstrate the effectiveness. © 2021 IEEE.

关键词： Controllers

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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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Random Fourier Features Based Kernel Risk Sensitive Loss Algorithm with Adaptive Moment Estimation Optimization Technology 22

Random Fourier Features Based Kernel Risk Sensitive Loss Alg...

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6th International Conference on Digital Signal processing, ICDSP 2022

作者： Wang, Daili Zheng, Yunfei Cai, Peng Liu, Qiang Shen, Minglin Wang, Shiyuan Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University China

ISBN: (纸本)9781450395809

Random Fourier features based kernel risk sensitive loss (RFFKRSL) is a popular nonlinear adaptive filtering algorithm developed in the random Fourier features space. The most attractive feature of such algorithm is that it would not cause the issue of linearly increasing network structure like the well-known kernel adaptive filtering algorithms, while having the ability to curb the negative influence induced by non-Gaussian noises. The stochastic gradient descent (SGD) method, however, is a default choice to determine the filtering coefficients of RFFKRSL, which can result in an undesirable convergence performance of the algorithm in many cases. To address this issue, two alternative optimization technologies, including adaptive moment estimation (Adam) and its extended version, i. e., Nesterov-accelerated Adam (Nadam), have been adopted to re-derive RFFKRSL. For simplicity, the proposed two algorithms are named as RFFKRSL with Adam (AdamRFFKRSL) and RFFKRSL with Nadam (NadamRFFKRSL), respectively. Although Adam and Nadam are common to deep neural network based learning methods, their applications to adaptive filtering are seldom to be seen, and the combination of them with RFFKRSL may open a new way to design nonlinear adaptive filtering algorithms that have been built with SGD method. Simulations on two time series prediction tasks are reported to demonstrate the desirable performance of the proposed algorithms. © 2022 ACM.

关键词： Stochastic systems

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A novel torus-based optical networks-on-chip exploiting double path communication algorithm 2

A novel torus-based optical networks-on-chip exploiting doub...

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2nd International Conference on Electronic information Engineering, Big Data, and Computer Technology, EIBDCT 2023

作者： Dai, Li Su, Ye Xie, Yiyuan School of Electronic and Information Engineering Southwest University Chongqing China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China

ISBN: (纸本)9781510664968

Optical networks-on-chip (ONoCs) using optical media to interconnect cores, have the advantages of high bandwidth, low power consumption and low latency. At present, mesh, torus and fat-tree are the most widely used topologies in ONoCs. Torus structure has the advantages of higher connectivity due to its annular structure. However, the traditional torus structure still has the problem of high end-to-end (ETE) delay. This paper proposes a new double-path ONoCs based on torus topology, named DPtorus. The DPtorus consists of two layers: one layer is a torus network divided into unit clusters, the other layer is an all-pass optical router. The dual-layer network is connected with each other by optical vias, so that there are two communication pathes between the source node and the target node in the network can be selected. The One is inter-cluster communication and the other is non-cluster communication. According to the comparison of the number of hop of the two communication paths, the communication path with fewer hops between the nodes is preferably selected to reduce the communication cost of the data packet. The network simulation results show that the DPtorus reduces latency and improves throughput compared to the torus network, resulting in better performance and enhanced reliability of network communications for the DPtorus. © 2023 SPIE.

关键词： Topology

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StO2 Stress Detection Based on Fewer Wavelengths through Linear Prediction Algorithm 6

StO2 Stress Detection Based on Fewer Wavelengths through Lin...

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6th IEEE International Conference on Computer and Communication Systems, ICCCS 2021

作者： Xiao, Xiao Liu, Xinyu Peng, Dairong Chen, Tong Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing400715 China

ISBN: (纸本)9780738126043

In recent years, tissue oxygen saturation (StO2) based on hyperspectral imaging (HSI) technology has been deeply studied in the field of affective computing. HSI StO2 is a kind of non-contact physiological signal, which can reveal people's potential emotions. However, at this stage, the number of bands to generate StO2 is too many to achieve real-time emotion detection. Therefore, based on the publicly available HSI stress database, we used a Linear Prediction (LP) algorithm to select only 8 characteristic bands from the original 106 bands to generate StO2 and performed the task of identifying psychological stress and physical stress. The experimental results showed that the recognition rate of StO2 generated based on the selected 8 bands in stress detection is very close to (even higher) that of the original 106 bands, and reaches 84.44% when using the Bayes classifier. © 2021 IEEE.

关键词： Hyperspectral imaging

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Centroid-Based Security Monitoring for Indoor Elderly Care with Millimeter Wave Radar 43

Centroid-Based Security Monitoring for Indoor Elderly Care w...

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43rd Chinese Control Conference, CCC 2024

作者： Huang, Chicheng Li, Chuandong Gao, Zelin Wu, Zhenyu Shi, Yawei Li, Huaqing Southwest University College of Electronic and Information Engineering Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing China

ISBN: (纸本)9789887581581

The increasing use of millimeter wave radar for smart elderly care is due to its precision, privacy, and cost-effectiveness. This technology enables real-time monitoring of unexpected incidents, particularly falls among the elderly indoors. By examining the relationship between cloud points and human centroids, this paper exploits the unique features of millimeter wave radar for personnel detection and human activity recognition. An improved Kalman filter algorithm for centroid tracking has been introduced. It effectively monitors the three-dimensional trajectory and velocity changes associated with various human behaviors. Subsequently, machine learning algorithms and neural networks are employed to classify these behaviors, including walking, sitting, and falling. Compared to conventional Kalman filtering, this approach effectively handles dispersion characteristics within point clouds, resulting in a smoother trajectory and more consistent centroid. This method enables the recognition of abnormal activities of people indoors with a maximum classification accuracy of 93.02%. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Kalman filters

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A Multiband Frequency Reconfigurable Antenna for Wireless Communication 43

A Multiband Frequency Reconfigurable Antenna for Wireless Co...

引用

43rd Chinese Control Conference, CCC 2024

作者： Liang, Rongkai Li, Chuandong Su, Youxun Liang, Weiwei Chen, Menggang Luo, Zhen Southwest University College of Electronic and Information Engineering Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing China

ISBN: (纸本)9789887581581

In order to enhance the adaptability of wireless devices across diverse applications, it becomes imperative for an antenna to embody a multitude of functionalities, including the capacity to dynamically reconfigure the operating frequency, polarization mode, and radiation pattern. This paper introduces a frequency-reconfigurable antenna that incorporates an L-U shaped slot band with a Split-Ring Resonator (SRR). Fabricated on a 1.2 mm low-cost FR4 substrate using a partially grounded design approach, which measures 40 × 35 mm2. By manipulating the bias states of the two PIN diodes, the radiation element current and field distributions can be altered, resulting in reconfigurable bands spanning 2.45 GHz, 3.3 GHz, 4.5 GHz, 7.4 GHz, and 9.4 GHz, with an expansive Ultra-Wide Bandwidth (UWB) of 4230 MHz. This antenna design caters to a range of wireless applications, including WLAN (Wireless Local Area Network), WiMAX (Worldwide Interoperability for Microwave Access), Remote Radio, and X-band Satellite Communication. Through meticulous simulation optimization, four reconfiguration scenarios are thoroughly examined by presenting and analyzing the simulation results. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Interoperability

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Effects of Negative Stimulation after Exercise on Frontal Asymmetry in Unregular Exercisers 6

Effects of Negative Stimulation after Exercise on Frontal As...

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2019 6th International Conference on Advanced Composite Materials and Manufacturing Engineering, ACMME 2019

作者： Wang, Tengfei Liu, Guangyuan School of Electronic and Information Engineering Southwest University Chongqing400700 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400700 China

As a signal to recognize emotion, the electroencephalogram (EEG) is used widely. Frontal asymmetry is not only related to emotion, but also affected by exercise. The purpose of our research is to explore the effects of exercise for negative emotion, and how the activity of the frontal of the college students who did not exercise regularly is. We used the frontal asymmetry between F3 and F4 channels of the alpha band. The result showed that the power of frontal asymmetry increased after exercise compared to that before exercise within 3 seconds after stimulation, and the change of the power during the 2nd second was more obvious. The activity of the frontal of the students without exercise habits can be altered by exercise. The frontal asymmetry is related to emotion, which confirms that exercise has an effect on the students without exercise habits after negative stimulation. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Students

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Cross-Subject Emotion Recognition with a Decision Tree Classifier Based on Sequential Backward Selection 11

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

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11th International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

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

ISBN: (纸本)9781728118598

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. © 2019 IEEE.

关键词： Emotion Recognition

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A Fusion Shallow and Deep Features Network for Facial StO2 Stress Classification 6

A Fusion Shallow and Deep Features Network for Facial StO2 S...

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6th IEEE information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Xia, Haolin Sun, Sirui Liu, Xinyu Zhou, Ju Wang, Hanpu Chen, Tong School of Electronic and Information Engineering Southwest University Chongqing China Key Laboratory of Non-Linear Circuit and Intelligent Information Processing of Chongqing Chongqing China Institute of Legal Psychology and Intelligent Computing Chongqing China

ISBN: (纸本)9781665460033

Stress is an emotional state that affects our lives, so it is vital to detect it accurately. Numerous studies have shown that tissue oxygen saturation (StO2) is an effective physiological signal for identifying different stress states. However, previous StO2 feature extraction methods relied too heavily on baselines to be realized in practice. In this paper, a two-stream network combining shallow and deep features, called CRNet, is proposed for baseline-independent StO2 stress classification. In CRNet, shallow features are extracted using a CNN network and deep features are extracted using a ResNet network. For the extracted high-dimensional deep features, MLP module is employed for dimensionality reduction, which can effectively combine the two levels of features and improve the feature extraction capability of the network. Experimental results show that CRNet can significantly improve the performance of StO2 stress classification to the state-of-the-art (SOTA) even when using only raw imbalanced data. © 2023 IEEE.

关键词： Feature extraction

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