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Compressive sensing-based super-resolution DOA estimation for mechanical scanning radar

JOURNAL OF ENGINEERING-JOE 2019年第21期2019卷 7800-7804页

作者： Cheng, Fanglei Wang, Hongyu Liu, Yang Beijing Inst Technol Sch Informat & Elect Beijing Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China

This study presents a novel super-resolution directions of arrival (DOA) estimation method for mechanical scanning radar by using the advanced compressive sensing algorithm. This method is implemented by constructing a signal model of the mechanical scanning radar through imitating the array radar signal model. Also then it established the compression relationship between the transmitted and received echo signals of the reader by sparsification technique of sending signals. Finally, the DOA estimation can be solved by employing advanced compressive sensing algorithm including basic pursuit (bp), orthogonal matching pursuit (OMP), regularised orthogonal matching pursuit algorithms and so on. Compared with the conventional super-resolution DOA estimation method such as multiple signal classification, the proposed method can distinguish two or more targets within one beamwidth more precisely. Compared with the earlier super-resolution DOA estimation method such as maximum likelihood, the proposed method can obtain more accurate and robust angle difference estimation and do not need to previously know the source number. Both simulated and experimental results show that the overall performance of the proposed DOA estimation is better than that of other methods.

关键词： direction-of-arrival estimation compressed sensing radar resolution radar receivers radar transmitters mechanical scanning radar arrival estimation method advanced compressive sensing algorithm array radar signal model regularised orthogonal matching pursuit algorithms multiple signal classification robust angle difference estimation received echo signal transmission compressive sensing-based super-resolution DOA estimation method directions of arrival estimation method received echo signal receiver sparsification technique bp algorithm basic pursuit algorithm OMP algorithm orthogonal matching pursuit algorithm maximum likelihood method

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The optimization method of CNC lathe performance based on Morris sensitivity analysis and improved GA algorithm

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JOURNAL OF VIBROENGINEERING 2024年第2期26卷 438-454页

作者： Li, Xianyi NingboTech Univ Sch Mechatron & Energy Engn Ningbo 315100 Peoples R China

This study achieved the goal of guiding bed design and optimization by conducting multi-objective optimization research on the performance of CNC lathe beds. In this study, Morris analysis was first performed on the sensitivity of the parameters, and then out to optimize the parameters using a combination of neural network and genetic algorithm. The loss function value, RMSE error accumulation, recall, sensitivity and specificity of the ASSGA-bp optimization model were better. The maximum error between the predicted and true values of the ASSGA-bp model was 0.28 mm. In the performance study of the multi-objective optimization method based on the Morris sensitivity analysis and the improved GA algorithm, the average MAE value is 0.91 %. The average RMSE value is 0.59 %. Also, the new model is significantly better than the NSGA-II, EGA, and FGA algorithms in terms of both the number of final non-dominated solutions and the speed of reaching convergence. The above results demonstrate that the model proposed in this study has high performance, can achieve faster convergence and has the best stability of the convergence state. The innovation of this article lies in the use of the Morris method to screen and evaluate numerous parameters in order to improve the accuracy of the calculation results and ensure the effectiveness of the optimization results. The improved algorithm overcomes the problems of bp neural network and can effectively improve the generalization performance of the neural network, thereby improving the prediction accuracy of the model.

关键词： Morris sensitivity GA algorithm bp algorithm CNC lathe parameter optimization

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Studies on the Possibility of Applying Artificial Neural Networks to Estimate Real Time Operation Parameters of Power Systems

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IFAC Proceedings Volumes 1997年第17期30卷 305-309页

作者： Shen Chen Sun Yuanzhang Lu Qiang Dept of E.E. Tsinghua Univ. Beijing 100084

In this paper, the possibility of utilizing artificial neural network (ANN) to estimate the real time operation parameters of power systems has been studied. The ANN which is used for estimation is a three-layer feedforward neural network. The inputs of the ANN are some locally measurable operation parameters of one system bus. The output of the ANN can be some synchronous parameters of some other remote buses. Simulation results show that a well trained ANN not only can estimate the real time operation parameters of remote buses with satisfying accuracy but also has great generalization abilities.

关键词： ANN bp algorithm power systems parameter estimation

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Near-Field Microwave Imaging with a New Optimization of MIMO Array

Near-Field Microwave Imaging with a New Optimization of MIMO...

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Asia-Pacific Microwave Conference

作者： Liechen Yu Shiyong Li Guoqiang Zhao Houjun Sun Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing Institute of Technology

ISBN: (纸本)9781479987689

The near-filed array-based imaging radar systems have been widely used in the field of concealed weapon detection, medical imaging, etc. However, conventional systems always require a large number of antenna elements. Both the cost and complexity of the systems are increased. This paper refers to the convolution principle and introduces an optimization method for near-filed MIMO array. And the back-projection (bp) algorithm is used to the near-field MIMO imaging, which can focus any array configurations. Simulations are provided to demonstrate the performance of the proposed method, which proves that it is an effective way to solve the near-field sparse array imaging problem.

关键词： Near-field Array-based MIMO Convolution prin-ciple bp algorithm

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MOGA algorithm for multi-objective optimization of aircraft detection

MOGA algorithm for multi-objective optimization of aircraft ...

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20th Congress of the International Commission for Optics

作者： Hongguang Sun1,2 Yuxue Pan2 Jingbo Zhang11 College of Computer, Northeast Normal University, ChangChun, 130024, China 2 ChangChun University of Science and Technology, ChangChun, 130022, China

This paper presents effective multi-objective genetic algorithms (MOGA) method, whose character lies in that evolutionary population is preference ranked based on concordance model, which was applied

关键词： multi-objective genetic algorithms objective recognition Pareto Optimal bp algorithm

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A learning algorithm of artificial neural network based on GA - PSO

A learning algorithm of artificial neural network based on G...

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6th World Congress on Intelligent Control and Automation

作者： Du, Shiqiang Li, Wanshe Cao, Kai Shaanxi Normal Univ Coll Math & Informat Sci Xian 710062 Peoples R China

ISBN: (纸本)1424403316

In order to get over the insufficiency of back-propagation (bp) algorithm, after analyses of genetic algorithm (GA) and particle swarm optimization (PSO), a GA-PSO algorithm is proposed. In GA-PSO, individuals in a new generation are created, not only by crossover and mutation operation in GA but also by PSO, based on redefine local optimization swarm. So it can both avoid local minimum and has good global search capacity. The performance of GA-PSO is compared to both GA and PSO in artificial neural networks weight training, demonstrating its superiority.

关键词： bp algorithm genetic algorithm particle swarm optimization GA-PSO algorithm

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Real-time digital simulation test system for power system relays based on bp neural network

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Diangong Jishu Xuebao/Transactions of China Electrotechnical Society 2004年第5期19卷 102-105页

作者： Tan, Wenzhong Wang, Xiaolan Lanzhou Univ. of Technol. Lanzhou 730050 China

This paper analyses the defects of relay testing simulator based on Electromagnetic Transient Program (EMTP) and puts forward the design scheme of portable real-time transient digital simulator (RTDS) based on DSP. Combined with a method of using wavelet to locate the transient fault and obtain its initial transient voltage U and phase θ, bp neural network is introduced to emulate transient fault progress. The study gives the following results: (I) Decreasing simulator parameters from four dimensions model f(R,L,θ,U) to one dimension f(R);(II) Simplifying algorithm of transient model and improving its real-time characteristic;(III) Simulating dynamically transient fault progress;(IV) Applying DSP into emulator and making (RTDS) portable in size.

关键词： bp algorithm DSP Dynamically testing RTDS Wavelet

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Simulation Study on Fuzzy Logic Neural-network Control in the AC Drive System

Simulation Study on Fuzzy Logic Neural-network Control in th...

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27th Chinese Control Conference

作者： Qiao Meiying Lan Jianyi Henan Polytech Univ Inst Elect Engn & Automat Jiaozuo 454000 Peoples R China Henan Polytech Univ Energy Sci & Engn Inst Jiaozuo 454000 Peoples R China

ISBN: (纸本)9787900719706

Based on the studying of the AC adjustment speed system and the complicated AC motor as controlled object, the method of fuzzy controller based neural-network is proposed in this paper. Simulations show that this method improved the ability of self-learning and anti-jamming of the AC adjustment speed system. The resumptive time of rotate speed in neural-network fuzzy control system is shorter than that in PID control system and the overshooting and oscillation during the recovery period are also weakened when the loads are suddenly increased or decreased. For systems with complicated structure, this method works well and also possesses high control accuracy under strong disturbances.

关键词： AC speed adjustment Neural-network control Fuzzy control bp algorithm

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The Research on the Fault Diagnosis for Boiler System Based on Fuzzy Neural Network

The Research on the Fault Diagnosis for Boiler System Based ...

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7th World Congress on Intelligent Control and Automation

作者： Zhao, Yawei Chen, Liang Yang, Qing Shenyang Ligong Univ Shenyang 110168 Peoples R China

ISBN: (纸本)9781424421138

The fuzzy logic was pulled in the neural network and the application of fault diagnosis for boiler system with the integrated fuzzy neural network is researched on the basic of the introductions of the basic principle of artificial neural network (ANN) and the principle of fault diagnosis for boiler system based on neural network. A example of training progress and testing results about the sample of boiler was given. And at last, it is proved that this integrated method can acquire a better result on fault diagnosis for boiler through error analysis compared with the traditional standard bp network.

关键词： fuzzy neural network bp algorithm fault diagnosis boiler system

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Research on Neural Networks Learning algorithm Based on PSO and COA

Research on Neural Networks Learning Algorithm Based on PSO ...

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31st Chinese Control Conference

作者： Wang Chen Chen Zengqiang Nankai Univ Dept Automat Tianjin 300071 Peoples R China

ISBN: (纸本)9789881563811

To the shortcoming of bp algorithm that solution is sensitive to initial value and easy to trap in local optima, this paper makes a research on Particle Swarm Optimization (PSO), Chaos Optimization algorithm (COA) and a modified Chaos Particle Swarm Optimization (CPSO) and applies them in neural networks learning problem. The mechanism of algorithms is explored in depth. A novel method of evaluating the degree of gathering for the swarm is proposed. The performance of algorithms is tested and analyzed by simulation and compared with bp algorithm. The results show that as novel neural networks learning algorithms, PSO and CPSO can overcome the defect of bp algorithm whose solution is sensitive to initial value and have the certain application value.

关键词： Neural Networks bp algorithm Particle Swarm optimization Chaos Optimization algorithm Chaos Particle Swarm Optimization Gather Value

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