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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Xu, Hangfei Chen, Hongyan Yuan, Kun China Jiliang Univ Coll Mech & Elect Engn Hangzhou 310018 Peoples R China

ISBN: (纸本)9783037853733

This paper introduces a method of constructing the control model of automatic windshield wiper based on bp neural network. A model of pattern recognition based on bp neural network is built and train it with specialists' experience data, and then tested it. The result indicates that this model based on bp neural network is effective to handle uncertainties and nonlinearities of the automatic windshield wiper system, without use of a sophisticated mathematical model.

关键词： bp neural network bp algorithm Automatic windshield wiper

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A Study on PID Control and Simulation Based on bp Neural Network

A Study on PID Control and Simulation Based on BP Neural Net...

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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Zhai Fangfang Ma Shaoli Liu Wei Hebei Chem & Pharmaceut Coll Dept Elect & Mech Engn Shihchiachuang Hebei Province Peoples R China Hebei Chem & Pharmaceut Coll Dept Personnel Shihchiachuang Hebei Province Peoples R China

ISBN: (纸本)9783037853696

This paper introduces the neural network PID control method, in which the parameters of PID controller is adjusted by the use of the self-study ability. And the PID controller can adapt itself actively. The dynamic bp algorithm of the three-layered network realizes the online real-time control, which displays the robustness of the PID control, and the capability of bp neural network to deal with nonlinear and uncertain system. A simulation is made by using of this method. The result of it shows that the neural network PID controller is better than the conventional one, and has higher accuracy and stronger adaptability, which can get the satisfied control result.

关键词： neural network bp algorithm PID control simulation

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Learning algorithm and hidden node selection scheme for local coupled feedforward neural network classifier

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NEUROCOMPUTING 2012年 79卷 158-163页

作者： Sun, Jianye Harbin Univ Sci & Technol Computat Ctr Harbin Peoples R China

In this paper, a neural classifier based on the newly developed local coupled feedforward neural network, which may improve the convergence of bp learning significantly, is developed. A binary threshold unit is used as the output node of the classifier. A general error gradient of the output node is defined for the bp training of the classifier. And a hidden node selection scheme is developed for the local coupled feedforward neural network. In addition, we derive a result on the "universal approximation" property of the local coupled feedforward neural network with an arbitrary group of window functions, which can cover the region of training samples. Simulation results show that the general error gradient and the hidden node selection scheme work well. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Neural network Classifier Gradient bp algorithm Hidden node LCFNN

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Road profile estimation using wavelet neural network and 7-DOF vehicle dynamic systems

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2012年第10期26卷 3029-3036页

作者： Solhmirzaei, Ali Azadi, Shahram Kazemi, Reza Mapna Locomot Co Tech & Engn Dept Mapna Grp Tehran Iran KN Toosi Univ Dept Mech Engn Tehran Iran

Road roughness is a broad term that incorporates everything from potholes and cracks to the random deviations that exist in a profile. To build a roughness index, road irregularities need to be measured first. Existing methods of gauging the roughness are based either on visual inspections or using one of a limited number of instrumented vehicles that can take physical measurements of the road irregularities. This paper more specifically focuses on the estimation of a road profile (i.e., along the "wheel track"). This paper proposes a solution to the road profile estimation using a wavelet neural network (WNN) approach. The method incorporates a WNN which is trained using the data obtained from a 7-DOF vehicle dynamic model in the MATLAB Simulink software to approximate road profiles via the accelerations picked up from the vehicle. In this paper, a novel WNN, multi-input and multi-output feed forward wavelet neural network is constructed. In the hidden layer, wavelet basis functions are used as activate function instead of the sigmoid function of feed forward network. The training formulas based on bp algorithm are mathematically derived and a training algorithm is presented. The study investigates the estimation capability of wavelet neural networks through comparison between some estimated and real road profiles in the form of actual road roughness.

关键词： Road profile Simulation Wavelet neural network bp algorithm Estimation

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A Morlet wavelet neural network-based online identification and control of coupled MIMO systems

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INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL 2012年第3-4期6卷 246-260页

作者： Varshney, Tarun Sheel, Satya MotiLal Nehru Natl Inst Technol Elect Engn Dept Allahabad 211004 Uttar Pradesh India

A new approach has been developed for the control of a coupled, non-linear MIMO system. A quasi-diagonal wavelet neural network (QDWNN)-based online identification and control scheme for coupled, non-linear MIMO system is presented in this paper. The new algorithm is based on control error process and does not need accurate mathematical model of the system to be controlled. Firstly an online parameter-tuning algorithm for multivariable PID-controllers is described and then it has been tested for two model systems. Simulation results show that the proposed control scheme minimises mean square error (MSE) and mean absolute error (MAE) remarkably, with reduced control effort, without slowing down the rise time.

关键词： quasi-diagonal wavelet neural network QDWNN MIMO system PID-tuning back propagation algorithm bp algorithm

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Study of the permanent magnetic Drive speed control system based on single-output PID neural network

Study of the permanent magnetic Drive speed control system b...

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4th International Conference on Multimedia Information Networking and Security (MINES)

作者： Shi, Songning Wang, Dazhi Northeastern Univ Sch Informat Sci & Engn Shenyang Liaoning Peoples R China

ISBN: (纸本)9780769548524

The single-output PID neural network control system is applied to Study of the permanent magnetic drive speed control system, the control system uses the bp algorithm to fix the connection weights through online training and learning, the objective function to reach the optimal value, in order to achieve the adaptive control of the permanent magnetic drive. The simulation results show that, on the permanent magnetic drive of this the nonlinear dynamic system control, single-output PID neural network control algorithm has a strong track performance and anti-load disturbance performance, can achieve good control.

关键词： PID neural network permanent magnetic drive bp algorithm nonlinear control

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Global Boundary Optimization for Automobile Engine Based on Genetic algorithm 1

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International Conference on Artificial Intelligence and Computational Intelligence (AICI 2012)

作者： Kong, Lifang Wang, Zhonghua Wang, Weikui AF Logist Acad Dept Basic Teaching Xuzhou 221008 Jiangsu Peoples R China Xuzhou Inst Technol Jiangsu Xuzhou 221008 Peoples R China

ISBN: (数字)9783642342400

ISBN: (纸本)9783642342394

In practical question, the standard to judge whether an engine performs properly is fuzzy, as it's difficult to give a critical value definitely. According to the engine condition and the complexity, uncertainty and nonlinear of the corresponding parameters, this paper proposed boundary optimization gradient genetic algorithm. In gradient genetic algorithm, bp algorithm of local search is introduced. The adaptive value of chromosomes group gets quickly improved with the search in one coding field getting avoided due to the utilization of knowledge of chromosomes in problem-domain. The crossover and mutation operations are added so that chromosomes will not fall into the local minimum point in neighborhood. Experiment indicates gradient genetic algorithm is a fast algorithm that can support the local optimization of individual chromosome and the global optimization of chromosomes in a group.

关键词： gradient genetic algorithm bp algorithm global optimization

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Joint De-modulation Decoding algorithm for LDPC-Coded BICM System

Joint De-modulation Decoding Algorithm for LDPC-Coded BICM S...

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International Conference on Frontiers in Computer Education (ICFCE 2011)

作者： Wang, Ying Jiang, Kangming Guangdong Power Dispatching & Controlling Ctr Dept Commun Guangzhou Guangdong Peoples R China

ISBN: (纸本)9783642275517

In order to improve the efficiency and decoding performance of LDPC-coded BICM system, the joint de-modulation Belief Propagation (JMbp) algorithm is proposed in this paper. Due to the good sparse structure of LDPC code, the JMbp algorithm can be derived from the generalized optimal bp algorithm based on the generalized distributive law (GDL). The JMbp algorithm has comparably low complexity while provides better decoding performance when compared with the traditional BICM-bp algorithm in high-ary modulated BICM systems. And the simulation results confirm that the JMbp algorithm outperforms the traditional BICM-bp algorithm over both the AWGN and Rayleigh fading channel.

关键词： LDPC code BICM system GDL bp algorithm

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Research on Welding Line Defect Recognition of the In-service Pipeline Using X-ray Detecting

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International Conference on Mechanical Engineering and Intelligent Systems (ICMEIS 2012)

作者： Yuan Peixin Zhang Congcong Yuan Yue Northeast Univ Coll Mech & Automat Shenyang Peoples R China

ISBN: (纸本)9783037854693

This paper, based on the practical demands of in-service pipeline detection, a set of X-ray digital image welding line defect intelligent recognition system is established. Taking the welding line image detected by X-ray as objects of study, self-adaptive median filter method filters noise, high frequency enhancement filter method conducts the image edge sharpening enhancement;a edge detection method for X-ray digital image based on morphological gradient is proposed;a group of characteristics parameters that accurately reflects the essence characteristic of defects is selected, using a self-organizing, self-adaptive three-layer feed-forward neural network, applying bp algorithm, the bp neural network recognition system is established, thus, to achieve detecticn and recognition of weld defects.

关键词： X-ray Digital image processing Edge detecting Feature extraction Neural network bp algorithm Weld defects recognition

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Image Transmission with UEP-LT over MIMO Channels

Image Transmission with UEP-LT over MIMO Channels

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2013 22nd Wireless and Optical Communication Conference

作者： Wuping Zhang Xiaorong Jing Zufan Zhang Qianbin Chen Chongqing Key Laboratory of Mobile Communication（CQUPT） Chongqing University of Posts and Telecommunications

ISBN: (纸本)9781467356985

The Luby Transform（LT） codes have been suggested as an efficient solution for multimedia communications over erasure packet network,and provide equal error protection（EEP） for all input ***,for the progressive image transmission,the significant source bits are generally located ahead of the bit streams of the encoder output,which are more important for the reconstruction of the ***,the LT codes based on EEP（EEP-LT） scheme is not suitable for the progressive image *** the paper,based on the LT codes,a novel unequal error protection（UEP） scheme is proposed for image transmission over multiple input multiple output（MIMO） channels,which is named UEP-LT *** results confirm the efficiency of the proposed scheme.

关键词： MIMO progressive source LT codes bp algorithm unequal error protection

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