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An optimization method for coupling matrix elements of microwave filter

An optimization method for coupling matrix elements of micro...

引用

Chinese control Conference

作者： Xiao-Long Zhuang Wei-Hua Cao Yan Yuan Can Liu Yu-Sheng Guo China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper proposes a coupling matrix element optimization method for microwave filters. The traditional method is more complex and does not directly optimize the filter coupling matrix elements. The firefly algorithm optimization method used in this paper directly optimizes the elements of the N + 2 order coupling matrix. Compared with the traditional method, it has better speed and optimization effect. First, the elements of the specific coupling matrix are introduced into the optimization algorithm to be executed, then the matrix is iterated through the set objective function. Finally, when the optimized data is within the allowable range, the optimization of the elements of the coupling matrix is stopped and optimization is performed. The resulting coupling matrix outputs the response. To prove the effectiveness of the proposed method, three methods were used to optimize the coupling matrix elements of the fourth-order filter and compare the final optimization results.

关键词： Couplings Tuning Transmission line matrix methods Integrated circuit modeling Optimization methods Cats

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RBF Neural Network Based-PID control for Weight on Bit During Drilling Operation

RBF Neural Network Based-PID Control for Weight on Bit Durin...

引用

Chinese control Conference

作者： Sike Ma Min Wu Luefeng Chen Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China

Deep drilling is a costly project and efficiency is of paramount importance. The weight on bit is one of the main operating parameters that influences the drilling efficiency and it was controlled by manual before. But after people saw the giant potential of an auto-drilling system in increasing the drilling efficiency, more and more studies on the feed back control of weight on bit have emerged. This paper mainly studied weight on bit dynamic under the variational formation based on a lumped parameter model and a self-tuning PID controller for weight on bit control. The parameters of the PID controller are tuned by using gradient descent method and RBF neural network identification.

关键词： Neural networks DC motors Feeds Suspensions Lifting equipment Torque Angular velocity

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Real-time optical music recognition for dulcimer robot 8

Real-time optical music recognition for dulcimer robot

引用

8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Xiao, Zhe Chen, Xin Zhou, Li School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Arts and Communication China University of Geosciences Wuhan430074 China

Optical music recognition (OMR) is an important technology to recognize paper music sheet automatically, which has been applied to preserve music scores. In this paper, we propose a real-time OMR system to recognize scores, and the recognized information is converted into a standard electronic music file to dulcimer robot, achieving real-time performance. During the recognition steps, we treat note group and isolated notes separately. The note group is decomposed into three fundamental elements: note stem, note head and note beams. And the isolated music symbol is recognized based on shape model descriptor. We conduct tests on five pages of music sheets, which are real images taken live by the camera. The tests show that the proposed method constitutes an interesting contribution to OMR. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Computer music

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Design and Characterization of An Ultralow-Potential Drift Ag/AgCl Electric Field Sensor

Design and Characterization of An Ultralow-Potential Drift A...

引用

Chinese control Conference

作者： Wang Luo Haobin Dong Jian Ge Huan Liu Bingjie Bar Cheng Zhang Zhiwen Yuan Jun Zhu Haiyang Zhang Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Wuhan Hubei China Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu China

This paper presents an all-solid porous Ag/AgCl electric field sensor with ultralow-potential drift for detecting the seafloor electric field signals. The superiority of porous electrode compared with flat electrode on the polarization stability is expounded, and the technological process using solid state agglomeration in developing the all-solid porous Ag/AgCl electrode core are described. Moreover, a new sensor shell is proposed. Numerous parameters, e.g., polarization resistance, self-potential, drift, etc., of the proposed electrode are tested. The experimental results show that the self-potential is less than ±0.1 mV, the source resistance is less than 0.01H, and the drift potential is less than ±5μV/24h, which indicate the superior performance of the proposed Ag/AgCl electric field sensor for marine electric field exploration.

关键词： Electrodes Electric potential Resistance Electric fields Solids Thermal stability Sea measurements

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Optimization of Overhauser magnetometer based on multi-channel frequency measurement algorithm

Optimization of Overhauser magnetometer based on multi-chann...

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Chinese control Conference (CCC)

作者： Guanzhong Wang Haobin Dong Jian Ge Vang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Wuhan Hubei China Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu China

Overhauser magnetometer is a weak magnetic measuring instrument based on the dynamic nuclear polarization of free radical species. It has the characteristics of high precision, high sensitivity, low power consumption and continuous measurement. It is widely used in geophysics, aeromagnetic surveying, satellite Magnetic measuring, military and various engineering fields. Aiming at the problem that the measurement accuracy of the magnetometer prototype is low and the measurement effect is poor when the angle between the probe axis and the geomagnetic field is 0°, several optimization methods are proposed and the magnetometer is optimized by adding the frequency measurement channel on the basis of the prototype. Based on the standard deviation of GSM-19 measurement data, comparing the experimental data that use the multi -channel frequency measurement algorithm, the standard deviation of prototype data decreases from 0.397 to 0.203 when the angle between probe axial and geomagnetic field is 45°, the standard deviation of the prototype data decreases from 0.631 to 0.371 when the angle between probe axial and geomagnetic field is 0°, which provides an important reference for the follow-up optimization of the magnetometer.

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EEG emotion recognition based on ensemble learning 8

EEG emotion recognition based on ensemble learning

引用

作者： Ding, Xue-Wen Liu, Zhen-Tao Feng, Zhi-Yong Xie, Qiao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Automotive Engineering Wuhan University of Technology Wuhan430070 China

EEG emotion recognition based on ensemble learning is proposed, in which three classification models including k-Nearest Neighbor, Decision Tree and Logistic Regression are integrated. In feature extraction, four kinds of features including Mean, Skewness, Sample Entropy and Lempel-Ziv complexity (LZC) are extracted from eight channels’ EEG signals, and Kernel Principal Component Analysis (KPCA) is employed to reduce the dimension of the feature set. The proposal is tested on the DEAP dataset in which the EEG emotional states are accessed in Arousal-Valence emotion space. The result shows that the average emotion recognition accuracies of 77.73% in Arousal dimension and 75.34% in Valence dimension are obtained, which demonstrates its feasibility. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Emotion Recognition

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Design and Characterization of An Ultralow-Potential Drift Ag/AgCl Electric Field Sensor

Design and Characterization of An Ultralow-Potential Drift A...

引用

第37届中国控制会议

作者： Wang Luo Haobin Dong Jian Ge Huan Liu Bingjie Bai Cheng Zhang Zhiwen Yuan Jun Zhu Haiyang Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Institute of Geophysics & Geomatics China University of Geosciences

This paper presents an all-solid porous Ag/Ag Cl electric field sensor with ultralow-potential drift for detecting the seafloor electric field signals. The superiority of porous electrode compared with flat electrode on the polarization stability is expounded, and the technological process using solid state agglomeration in developing the all-solid porous Ag/Ag Cl electrode core are described. Moreover, a new sensor shell is proposed. Numerous parameters, e.g., polarization resistance, self-potential, drift, etc., of the proposed electrode are tested. The experimental results show that the self-potential is less than ± 0.1 m V, the source resistance is less than 0.01Ω, and the drift potential is less than ±5μV/24 h, which indicate the superior performance of the proposed Ag/Ag Cl electric field sensor for marine electric field exploration.

关键词： Ag/AgCl electrode pair ultralow-potential drift electric filed sensor stability

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Chaotic Oscillator Based on a Modified Voltage-controlled HP Memristor Model

Chaotic Oscillator Based on a Modified Voltage-Controlled HP...

引用

IEEE advanced Information Management,Communicates,Electronic and automation control Conference (IMCEC)

作者： Zhen Wang Chao Sun Fang Jin Wenqin Mo Junlei Song Kaifeng Dong Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Different from previous studies on memristive chaotic oscillators which tended to adopt common mathematical models but lacked practical consideration, in this paper, a novel memristive chaotic oscillator based on a modified voltage-controlled HP memristor model was proposed for the first time. By replacing Chua's diode with this model in a canonical Chua's circuit, we derived an oscillator characterized by rich dynamics such as special-shaped attractors, a wide range of chaos and insensitivity to the initial value of the memristor. These features were systematically investigated in terms of bifurcation diagrams, Poincaré map, time series, Lyapunov exponents, etc.

关键词： automation

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Electroencephalogram Emotion Recognition Based on A Stacking Classification Model

Electroencephalogram Emotion Recognition Based on A Stacking...

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Chinese control Conference (CCC)

作者： Oiao Xie Zhen-Tao Liu Xue-Wen Ding Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

To improve the accuracy of Electroencephalogram (EEG) emotion recognition, a stacking emotion classification model is proposed, in which different classification models such as XGBoost, LightGBM and Random Forest are integrated to learn the features. In addition, the Renyi entropy of 32 channels' EEG signals are extracted as the feature and Linear discriminant analysis (LDA) is employed to reduce the dimension of the feature set. The proposal is tested on the DEAP dataset, and the EEG emotional states are accessed in Arousal-Valence emotion space, in which HA/LA and HV/LV are classified, respectively. The result shows that the average recognition accuracies of 77.19% for HA/LA and 79.06% for HV/LV are obtained, which demonstrates that the proposal is feasible in EEG emotion recognition.

关键词： Electroencephalography Emotion recognition Brain modeling Feature extraction Stacking Entropy Predictive models

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Speech Emotion Recognition Based on Linear Discriminant Analysis and Support Vector Machine Decision Tree

Speech Emotion Recognition Based on Linear Discriminant Anal...

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Chinese control Conference (CCC)

作者： Jun-Wei Mao Yong He Zhen-Tao Liu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

For speech emotion recognition, emotional feature set with high dimension may produce redundant features and influence the recognition accuracy. To solve this problem and obtain the optimal emotional feature subset of speech, a feature dimension reduction based on linear discriminant analysis is proposed. According to the confusion degree between different basic emotions, an emotion recognition method based on support vector machine decision tree is proposed. Experiment on speaker-dependent speech emotion recognition using Chinese speech database from institute of automation of Chinese academy of sciences is performed and a speech emotion recognition system is presented, where standard feature sets of the INTER-SPEECH and classic classifiers are used in comparative experiments respectively. Experimental results show that the proposal achieves 84.39% recognition accuracy on average. By proposal, it would be fast and efficient to discriminate emotional states of diverse speakers from speech, and it would make it possible to realize the interaction between speaker and computer/robot in the future.

关键词： Feature extraction Support vector machines Speech recognition Emotion recognition Decision trees Dimensionality reduction Linear discriminant analysis

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