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network learning algorithm
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  网络学习算法
     An Original RBF Network Learning Algorithm
     一种新颖的径向基函数(RBF)网络学习算法
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     Research on BP Network Learning Algorithm and Application in Picture Pattern-recognition
     BP网络学习算法研究及其图像模式识别应用
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     A BP neural network learning algorithm based on differential evolution
     基于差分进化的BP网络学习算法
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     The Study of Improvedment Plans of BP Neural Network Learning Algorithm
     BP网络学习算法改进方案的探析
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     A RBF Neural Network Learning Algorithm Based on Improved PSO
     一种改进的粒子群优化RBF网络学习算法
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  “network learning algorithm”译为未确定词的双语例句
     An Improved I-B&B-MDL-based Bayesian Network Learning Algorithm
     基于I-B&B-MDL的贝叶斯网结构学习改进算法
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     A Neural Network Learning Algorithm for PCA and MCA
     一种用于PCA与MCA的神经网络学习算法
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     Study on the Application of RBF Neural Network Learning Algorithm for Pattern Classification
     RBF神经网络学习算法在模式分类中的应用研究
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     A Neural Network Learning Algorithm Based on the Extended Kalman Filter Applied to Stock Prediction
     基于扩展Kalman滤波的神经网络学习算法在股票预测中的应用
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     A Neural Network Learning Algorithm Based on Direction of Inner Product and Its Application
     基于内积方向的神经网络学习算法及应用
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  相似匹配句对
     Learning with Network——E-Learning
     网络化学习——E-Learning
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     c network.
     针对特殊的网络分析了纳什均衡的性质;
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     NETWORK
     网络
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     Network-based individualized learning
     基于网络的个别化学习研究
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     On Learning
     论学习
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  network learning algorithm
Optimal PID gains can be learned by a neural network learning algorithm and then a simple standard fuzzy control could be incorporated in the overall control strategy, if needed, for enhancing the system responses.
      
We apply the hybrid Genetic/Random Neural Network learning algorithm to two pattern recognition problems.
      
In this paper, we propose to solve the patterns recognition problem using a hybrid Genetic/Random Neural Network learning algorithm.
      
Resolution of pattern recognition problems using a hybrid Genetic/Random Neural Network learning algorithm
      
This letter analyzes the reasons why the known Neural Back Promulgation (NBP) network learning algorithm has slower speed and greater sample error.
      
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This paper presents a new multilayer feedforward neural networks learning algorithm. It is of exponential convergence speed and also applicable for the illconditioned stuations.This algorithm is simple, easy to use, and its convergence is discussed, too.Example result indicate effectiveness of thealgorithm.

针对目前常用的多层前馈神经元网络的BP学习算法的收敛速度慢、易出现病态情况、且容易陷入局部极小点的缺点,提出了一种新的多层前馈神经元网络训练算法。该算法具有指数收敛速度,能克服病态,算法简单,易于应用,并且给出了该算法收敛性的证明。实例分析验证了算法的有效性。

P neural network learning algorithm is analyzed.Additional momentum term,grouPs training and synthesis are used to improve BP neural network learning speed,and evidenteffect is obtained.

本文在深入分析了BP人工神经网络学习算法的基础上,研究了采用加动量项法、成批训练法及综合法来提高BP网络的学习速度,取得了显著效果.

This paper presents a new multilayer feedforward neural networks learning algorithm. It is of exponential convergent speed,and also applicable for the ill-conditioned situations. Its convergence is discussed too The practical resuits indicate effectiveness of the algorithm.

提出了一种多层前馈神经元网络训练算法.该算法具有指数收敛速度、能克服病态、简单易用.并给出一种计算水电站下游的不稳定流的神经元网络方法,实例证明其有效性.

 
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