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神经网络与免疫算法的结合，用matlab编程实现一些小功能-Neural network with a combination of immune algorithm with matlab programming to achieve some small features
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人工神经网络(ANN)的泛化特性是神经网络最重要的特性,同时也是最不容易保证的特性。本程序对改进泛化的神经网络算法以及新兴的机器学习算法——支持向量机算法进行研究,-Artificial Neural Network (ANN) the generalization characteristics of neural networks are the most important characteristics, but also not easy to guarantee the most f
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利用BP神经网络对遥感图像进行地物的自动识别-The use of BP neural network of remote sensing images of the automatic recognition of features
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a transmission line fault location model which is based on an Elman recurrent network
(ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with
different inception times are implemented on a 380-kV proto
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BP神经网络 数据分类 语音特征信号分类-BP neural network classification of data signal classification speech features
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人工神经网络就是模拟人思维的第二种方式。这是一个非线性动力学系统，其特色在于信息的分布式存储和并行协同处理。虽然单个神经元的结构极其简单，功能有限，但大量神经元构成的网络系统所能实现的行为却是极其丰富多彩的。
-Simulation of artificial neural network is a second way of human thinking. This is a nonlinear dynamic system, which features a distributed i
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人工神经网络的matlab实现，可以实现分类、预测等多种功能。-Matlab implementation of artificial neural network can achieve classification, prediction and other features.
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Matlab神经网络算法中的BP神经网络算法在语音特征信号分类应用的源程序。-BP neural network algorithm in the Matlab neural network algorithm source signal classification applications in speech features.
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In this paper, an attractive approach for teaching genetic algorithm has been
presented. This approach is based primarily on using MATLAB in
implementing the genetic operators: crossover, mutation, and selection. An
advantage of using such an a
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This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot
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应用matlab的GUI设计功能，设计神经网络-Application matlab GUI design features, design neural network
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In this report, we devise a methodology for identifying the species of an iris amongst 3 based on 4 distinctive features. We first cover the constitution of the data set and input patterns. We then determine the layout and structure of the neural net
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一个简易的神经网络模型，
一个对象具有4种特征，现设有3个对象，学习完成后，输入4个特征数据，能够得到属于哪一个对象类型(A simple neural network model,
An object has 4 features, and now has 3 objects, after learning, input 4 characteristic data, which type of object can be obtained)
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