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Design of twodimensional digital filters using neural networks

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Journal of Systems Engineering and Electronics 2005年第4期16卷 767-771页

A new approach for the design of two-dimensional （2-D） linear phase FIR digital filters based on a new neural networks algorithm （NNA） is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations.

关键词： 2-D linear-phase FIR digital filters neural network convergence theorem stability.

Steganography based on wavelet transform and modulus function

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Journal of Systems Engineering and Electronics 2007年第3期18卷 628-632页

作者： Kang Zhiwei Liu Jing he yigang School of Computer and Communication Hunan Univ. Changsha 410082 P. R. China School of Electrical and Information Engineering Hunan Univ. Changsha 410082 P. R. China

In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image, in accordance with the visual property that human eyes are less sensitive to strong texture, a novel steganographic method based on wavelet and modulus function is presented. First, an image is divided into blocks of prescribed size, and every block is decomposed into one-level wavelet. Then, the capacity of the hidden secret data is decided with the number of wavelet coefficients of larger magnitude. Finally, secret information is embedded by steganography based on modulus function. From the experimental results, the proposed method hides much more information and maintains a good visual quality of stego-image. Besides, the embedded data can be extracted from the stego-image without referencing the original image.

关键词： steganography capacity wavelet transform modulus function HVS.

Multi-period Two-stage Robust Optimization of Radial Distribution System with Cables Considering Time-of-use Price

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 312-323页

作者： Jian Zhang Mingjian Cui yigang he Fangxing Li School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China University of Tennessee KnoxvilleTN 37996USA School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the regulation equipment,and the current of the shunt capacitor of the cables are not *** this paper,a multi-period two-stage robust scheduling strategy that aims to minimize the total cost of the power supply is *** strategy considers the time-ofuse price,the capability of the DGs to regulate the active and reactive power,the action costs of the regulation equipment,and the current of the shunt capacitors of the cables in a radial distribution ***,the numbers of variables and constraints in the first-stage model remain constant during the iteration to enhance the computation *** solve the second-stage model,only the model of each period needs to be ***,their objective values are accumulated,revealing that the computation rate using the proposed method is much higher than that of existing *** effectiveness of the proposed method is validated by actual 4-bus,IEEE 33-bus,and PG 69-bus distribution systems.

关键词： Distribution system robust optimization mixed-integer second-order cone programming cost of regulation equipment coordinated optimization of active and reactive power

Primal dual interior point dynamic programming for coordinated charging of electric vehicles

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Journal of Modern Power Systems and Clean Energy 2017年第6期5卷 1004-1015页

作者： Jian ZHANG yigang he Mingjian CUI Yongling LU hefei University of Technology Hefei 230009China University of Texas at Dallas RichardsonTX 75080USA State Grid Jiangsu Electric Power Company Research Institute Nanjing 211103JiangsuChina

Coordinated charging of electric vehicles(EVs)is critical to provide safe and cost effective operation of distribution systems where household single phase charging of EV could contribute to imbalance of the distribution *** date,reported researches on optimization methods for coordinated charging aiming at minimizing power losses have the disadvantages of low calculation efficiency when applied to large systems or have not taken the voltage constraints into *** phase component and polar coordinates power flow equations of an unbalanced distribution system are *** dual interior point dynamic programming is introduced for coordinated charging of EVs to minimize distribution system losses where charging demand,voltage and current constraints have been taken into *** proposed optimization is evaluated using an actual 423-bus case as the test *** are promisingwith the proposed method having good convergence under time-efficient calculations while providing optimization of power losses,lower load variance,and improvement of voltage profile versus uncoordinated scenarios.

关键词： Electric vehicles(EVs) Coordinated charging Primal dual interior point programming Distribution system Power losses

An Adaptive SVD Method for Solving the Pass-Region Problem in S-Transform Time-Frequency Filters

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Chinese Journal of Electronics 2015年第1期24卷 115-123页

作者： YIN Baiqiang he yigang LI Bing ZUO Lei YUAN Lifen School of Electrical and Automation Engineering Hefei University of Technology

S-transform(ST) is an excellent tool for time-frequency filter. There are two factors that influence filtering performance: Inverse s-transform(IST) algorithms and the pass-regions in time-frequency domain. A novel matrix IST algorithm is derived and an adaptive Singular value decomposition(SVD) method for solving the pass-region problem is proposed. The former can avoid reconstructing errors in time-frequency filtering; the latter is effective to distinguish the pass-region of signal from *** can be realized by removing the smaller singular values and keeping the larger singular values. An additive noise perturbation model is built in ST time-frequency domain and the effective rank of noise perturbation model based on matrix IST is analyzed. Simulation results indicate that the proposed SVD method can provide higher precision than the existing ones at low signal-to-noise ratio and does not need to compute the noise statistics *** examples verify the effectiveness of proposed method.

关键词： S-transform Matrix inverse S-transform Time frequency filter Singular value decomposition.

A novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder for small negative samples

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High Voltage 2022年第5期7卷 925-935页

作者： Fangming Deng Wei Luo Baoquan Wei Yong Zuo Han Zeng yigang he State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong UniversityNanchangChina School of Electrical and Automation Engineering East China Jiaotong UniversityNanchangChina School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative *** proposed DCAE scheme combines the advantages of supervised learning and unsupervised *** order to reduce the high cost of training Deep Neural Networks,this paper pre-trained the Convolutional Neural Networks(CNN)through open labelled *** transferring learning,the encoder part of the traditional Convolutional Auto-Encoder was replaced by the first three layers of the CNN,and a small number of defect samples were used to fine-tune the parameters.A threshold discrimination scheme was designed to evaluate the model detection,realising the self-explosion detection of insulator by judging the residual result and abnormal *** experimental results show that compared with the existing insulator self-explosion detection schemes,the proposed scheme can reduce the model training time by up to 40%,and the recognition accuracy can reach 97%.Moreover,this model does not need a large number of insulator labelled data and is especially suitable for small negative sample application.

关键词： scheme insulator defect

A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction

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Green Energy and Intelligent Transportation 2024年第2期3卷 50-59页

作者： Yuan Chen Wenxian Duan yigang he Shunli Wang Carlos Fernandez School of Artificial Intelligence Anhui UniversityHefei 230009China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430000China School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China School of Pharmacy and Life Sciences Robert Gordon UniversityAberdeenAB10-7GJUK

Battery life prediction is of great significance to the safe operation,and reduces the maintenance *** paper proposes a hybrid framework considering feature extraction to achieve more accurate and stable life prediction performance of the *** feature extraction,eight features are obtained to fed into the life prediction *** hybrid framework combines variational mode decomposition,the multi-kernel support vector regression model and the improved sparrow search algorithm to solve the problem of data backward,uneven distribution of high-dimensional feature space and the local escape ability,*** parameters of the estimation model are obtained by introducing the elite chaotic opposition-learning strategy and adaptive weights to optimize the sparrow search *** algorithm can improve the local escape ability and convergence performance and find the global *** comparison is conducted by dataset from National Aeronautics and Space Administration which shows that the proposed framework has a more accurate and stable prediction *** with other algorithms,the SOH estimation accuracy of the proposed algorithm is improved by 0.16%–1.67%.With the advance of the start point,the RUL prediction accuracy of the proposed algorithm does not change much.

关键词： State of heath Improved sparrow search algorithm Remaining useful life Variational mode decomposition Multi-kernel support vector regression Feature extraction

Optimal Control of Three-wheel Steering Forklift with Steer-by-Wire 36

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Optimal Control of Three-wheel Steering Forklift with Steer-...

A linear ridgelet network approach for fault diagnosis of analog circuit

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作者： Yang Liu Benxian Xiao Zhizheng Jiang yigang he School of Electrical Engineering and Automation Hefei University of Technology Institute of Industry & Equipment Technology Hefei University of Technology

ISBN: (纸本)9781538629185

In order to improve the deficiency of traditional forklift steering system,dynamic model of two degree of freedom for three-wheel forklift is *** optimization of yaw rate is based on driver-forklift close-loop,and adopts comprehensive evaluation indexes of forklift handling and stability and genetic *** objective of this method is to zero sideslip angle and track the optimal yaw rate,and the sliding mode controller is designed to actively control steering angle of front and rear *** gain fuzzy modulation is developed to reduce *** closed-loop double-shift line simulation experiment with the front-rear wheel proportional control is carried out in MATLAB at the same *** results of simulation show that the three-wheel forklift under sliding mode control can achieve the control objective of both reducing the sideslip angle and tracking desired yaw rate,and improve the handling and stability of forklift,and effectively reduce the driver’s driving burden.

关键词： Three-wheel steering steer-by-wire system genetic algorithm sliding mode control chattering suppression handling stability

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Science China(Information Sciences) 2010年第11期53卷 2251-2264页

作者： XIAO YingQun& he yigang College of Electrical and Information Engineering, Hunan University, Changsha 410082, China College of Electrical and Information Engineering Hunan University Changsha China

A linear ridgelet network combining ridgelet, linear term and the standard feed-forward neural network used for diagnosing the faults of analog circuit is constructed, and a training algorithm based on the steepest gradient descent method and momentum method for this network and the procedure for diagnosing these faults are proposed. The resulting linear ridgelet network can learn more rapidly from training samples and handle more effectively the complicated fault information of circuit under test than wavelet network and ridgelet network, classifying these faults effeciently and correctly and achieving a high classification accuracy. The simulation results demonstrate the effectiveness of this approach.

关键词： fault diagnosis of analog circuit ridgelet linear ridgelet network wavelet packet decomposition