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检索条件"主题词=Bp algorithm"

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

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

引用

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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APPLICATION OF FREQUENCY DOMAIN QUANTITATIVE ANALYSIS IN THE DIAGNOSIS OF CARDIAC DISEASES

APPLICATION OF FREQUENCY DOMAIN QUANTITATIVE ANALYSIS IN THE...

引用

Conference on Image Processing - Medical Imaging 1995

作者： SUN, Y LI, XL LIAO, MY DONG, Z WANG, XF WANG, JE XIE, MX MCMASTER UNIV DEPT ELECT & COMP ENGNHAMILTONON L8S 4K1CANADA

ISBN: (纸本)0819417823

Cardiac B-mode ultrasonic tissue characterization is designed to use the fluctuations in acoustic signals from the myocardium to differentiate normal from morbid tissues due to their characteristic texture attenuation. In our paper, we suggest a new way that is based on frequency-domain texture analysis to quantify tissue characterization. The results of our experiments indicate that three of the power spectrum features PSE, PSM and LT can describe the characterization of myocardiac tissue very well either in normal or in diseased condition. We select these three features together with another feature PSER derived by combining two PSE values to construct a multilayered neural network based on bp algorithm which acts as a classifier to diagnose automatically input image samples of various diseases after being trained with known samples. The performance of the classifier is very satisfactory. In short, our system opens a new way for the quantitative diagnostic detection of diverse diseases including coronary heart disease myocardial infarction (CHD-MI) and dilated cardiomyopathy (DC).

关键词： FREQUENCY DOMAIN ANALYSIS TEXTURE ANALYSIS NEURAL NETWORK bp algorithm T-TESTING B-MODE ULTRASONIC IMAGE CARDIAC DISEASE AUTOMATIC DIAGNOSIS

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Pitch recognition based on intelligent neural network system

Pitch recognition based on intelligent neural network system

引用

International Conference on Communications, Circuits and Systems

作者： Li, MY Li, T Sichuan Univ Dept Comp Chengdu 610065 Peoples R China

ISBN: (纸本)0780386477

Most pitch detection algorithms are based on the relationship between frequency and note, however, when the pitch is hummed by an untrained person, the accuracy of pitch recognition would decline obviously. A new intelligent pitch recognition (IPR) method based on intelligent neural networks is presented. Using the ideas of intelligent neural networks, a complex task of pitch recognition can be divided into several simple ones, which can be easily implemented by some simple intelligent neuron respectively. Then a large network built out of those intelligent neurons can solve the original, complex problem and the work is much easier than those traditional neural network methods. Experimental results show it is a good way for the pitch recognition.

关键词： neural network pitch-recognition wavelet transform bp algorithm

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Krasnosel'skii-Pokrovskii Hysteresis Model for Magnetic Shape Memory Alloy Actuator 35

Krasnosel'skii-Pokrovskii Hysteresis Model for Magnetic Shap...

引用

第35届中国控制会议

作者： ZHOU Miaolei HAN Tingting ZHANG Qi College of Communication Engineering Jilin University

ISBN: (纸本)9781509009107

Magnetic shape memory alloy actuator have hysteresis characteristics, in order to describe the hysteresis nonlinearity of magnetic shape memory alloy actuator and study the methods of eliminating the hysteresis nonlinearity of magnetic shape memory alloy actuator, the Krasnosel'skii-Pokrovskii(KP) model is firstly established in this paper. Secondly, bp neural network and adaptive linear neural network are applied to identify the density functions of the KP model respectively. Finally, it is obtained that the modeling accuracy of the KP model is 0.37% by bp algorithm and the modeling accuracy of the KP model based on adaptive linear neural network is 0.19% through the simulation results, which prove that the KP model can characterize the hysteresis nonlinearity of magnetic shape memory alloy actuator.

关键词： Magnetic shape memory alloy actuator hysteresis nonlinearity bp algorithm Krasnosel'skii-Pokrovskii model adaptive linear neural network

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A new evolutionary neural network and its application for the extraction of vegetation anomalies

引用

2nd International Symposium on Intelligence Computation and Application (ISICA 2007)

作者： Guo, Yan Kang, Lishan Liu, Fujiang Mei, Linlu China Univ Geosci Sch Comp Lumo Rd 388 Wuhan 430074 Peoples R China China Univ Geosciences Fac Informat Engn Wuhan Peoples R China Wuhan Univ Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9783540745808

This paper proposes an evolutionary neural network (ENN). In this ENN model evolutionary algorithms (EAs) are adopted to train the multilayer perceptrons (MLPs) to overcome backpropagation (bp) algorithm shortcomings. The proposed ENN technique was used to the extraction of vegetation anomalies in remote sensing imagery compared against MLPs with bp algorithm. The experiments of extracting vegetation anomalies were carried out by ENN classifiers and bp classifiers in a 1241x1149 pixel Landsat-7 Enhanced Thematic Mapper plus (ETM+) high-resolution image of Zhaoyuan gold deposits, Shandong, China. We found that the use of EAs for finding the optimal weights of MLPs results mainly in improvements in overall accuracy of MLPs.

关键词： evolutionary neural networks evolutionary algorithms bp algorithm vegetation anomalies extraction remote sensing

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Prediction of coiling temperature of hot rolled strip based on neural network 6

Prediction of coiling temperature of hot rolled strip based ...

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6th International Conference on Fluid Power Transmission and Control (ICFP 2005)

作者： Wang, YQ Wang, HF Zhu, DD Yanshan Univ Coll Mech Engn Qinhuangdao Peoples R China

ISBN: (纸本)7506274027

Hot strip coiling temperature is one important parameter of performance index in hot rolled strip, and its control system is highly nonlinear. The coiling temperature of hot rolled strip is exactly predicted based on neural network (NN) by means of its approximation to any non-linear system and its ability of approximation to any nonlinear system and its ability of prediction. Additional momentum method, which is an improved bp algorithm, is used in the NN. A new coiling temperature control system based on NN combined with mathematical model is presented. Its feed-forward control is based on the NN, and its feed-backward control is based on mathematic model. Finally, the prediction by the NN shows that the control performance is satisfactory, and it can make mathematical model of coiling temperature identified.

关键词： hot rolled strip laminar cooling bp algorithm neural network

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Artificial Neural Networks with Ant Colony Optimization for Assessing Performance of Residential Buildings

Artificial Neural Networks with Ant Colony Optimization for ...

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International Conference on Future BioMedical Information Engineering

作者： Shi, Huawang Li, Wanqing Hebei Univ Engn Sch Civil Engn Handan 056038 Hebei Peoples R China Hebei Univ Engn Coll Econ & Management Hebei 056038 Peoples R China

ISBN: (纸本)9781424446902

This article established artificial neural networks based on improved ant colony optimization evaluation model for residential performance. Firstly, on the basis of comprehensive analysis of the effects factors of residential building's performance, considering of the advantages of dealing with non-linear object of neural network, the neural network is trained by the sample data. While training neural network, the bp algorithm has good local performance but it is easy to fall into local Minimum, and the ant colony algorithm has good global performance, so the following combinatorial method is put forward. Then, the neural network is trained based on ant colony algorithm (ACbp algorithm) in global space, the parameters of neural network is trained using bp algorithm in local space. At last, a case study carried out on the performance assessment of sample residential buildings using the model shows that the ACbp neural network outperforms bp neural network and AC neural network in the aspect of dynamic error forecast is verified by computer emulation example, and related conclusions are given.

关键词： neural network ant colony algorithm bp algorithm residential buildings performance assessment

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The study on neural network intelligent method based on genetic algorithm

The study on neural network intelligent method based on gene...

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International Conference on Advanced Materials and Information Technology Processing (AMITP 2011)

作者： Wang, Hongtao Wuhan Univ Technol Network Informat Ctr Wuhan 430070 Peoples R China

ISBN: (纸本)9783037851579

The paper gives the hybrid computational intelligence learning algorithm with global convergence, which is combined by bp algorithm and genetic algorithm. This algorithm connects the strengths of the bp algorithm and genetic algorithms. It not only has faster convergence, but also has a good global convergence property. The computer simulation results show that the hybrid algorithm is significantly better than the genetic algorithm and bp algorithm.

关键词： neural network bp algorithm genetic algorithm global convergence

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A Multi-level Artificial Neural Network for Gasoline Demand Forecasting of Iran

A Multi-level Artificial Neural Network for Gasoline Demand ...

引用

2nd International Conference on Computer and Electrical Engineering

作者： Kazemi, A. Shakouri G, H. Mehregan, M. R. Taghizadeh, M. R. Menhaj, M. B. Foroughi.A, A. Univ Tehran Tehran Iran Amirkabir Univ Technol Tehran Iran Natl Iranian Oil Co Tehran Iran

ISBN: (纸本)9780769539256

This paper presents a neuro-based approach for Iran annual gasoline demand forecasting by several socioeconomic indicators. In order to analyze the influnce of economic and social indicators on the gasoline demand, the gross domestic product (GDP), the population and the total number of vehicles are selected. This approach is structured as a multi-level artificial neural network (ANN) based on supervised multi-layer perceptron (MLP), trained with the backpropagation (bp) algorithm. This multi-level ANN is designed properly. Actual data of Iran from 1968-2006 is used to train the multi-level ANN and illustrate capability of the approach in this regard. Comparison of the model predictions with data of the evaluating period shows validity of the model. Furthermore, the demand for the period of 2007 to 2030 is estimated.

关键词： ANN MLP bp algorithm Forecasting Gasoline demand

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Study on Calibrating Method of FOB Position Tracker Based on Neural Network

Study on Calibrating Method of FOB Position Tracker Based on...

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Li, Shanshan Zhu, Zhongxiang Liu, Bo Song, Zhenghe Mao, Enrong Shangguan, Lantian China Agr Univ Beijing Key Lab Optimal Design Modern Agr Equipme Beijing 100083 Peoples R China

ISBN: (纸本)9783038351153

Due to the instability and low precision of electromagnetic position trackers and the inefficiency of existing calibrating methods, a method with high accuracy and effectiveness for FOB (Flock of Birds) calibration was studied. The components, operational principle, merits and drawbacks of FOB were briefly introduced. The positions of 343 sampling points set in the effective working area were measured and the data was processed for trainings and tests of the calibration model established using genetic algorithm and bp algorithm. Experiments were conducted to verify the effectiveness of the method and the results showed the calibrated tracker's average errors in the X, Y, and Z direction were 0.86cm, 0.70cm and 0.83cm respectively, meeting the requirements of human-computer interaction.

关键词： Neural network FOB Calibration Genetic algorithm bp algorithm

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