Description: This book is about the use of artificial neural networks for supervised learning problems. Many such problems occur in practical applications of artificial neural networks. For example, a neural network might be used as a component of a face recognition system for a security appli-
cation. After seeing a number of images of legitimate users' faces, the network needs to determine accurately whether a new image corresponds to the face of a legitimate user or an imposter. In other applications, such as the prediction of future price of shares on the stock exchange, we may require a neural network to model the relationship between a pattern and a real-valued quantity. Platform: |
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Author:kj5566 |
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Description: 基于ELMAN神经网络对阶跃响应动态进行补偿也可以举一反三的运用于ELMAN网络的其他应用-Elman neural network based on the step response of the dynamic compensation can be applied to an example of the Elman network other applications Platform: |
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Author:陈俊宏 |
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Description: 这是一个matlab实现第归神经网络的例子, 实现的第归神经网络是 : Real Time Recurrent Learning-This is a Matlab achieve its neural network naturalization example, the realization of naturalization neural network is : Real Time Learning Recurrent Platform: |
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Author:王世海 |
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Description: The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring
different adaptation algorithms.~..~
There are 11 blocks that implement basically these 5 kinds of neural networks:
1) Adaptive Linear Network (ADALINE)
2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA)
3) Radial Basis Functions (RBF) Networks
4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN)
5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm
A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included-The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms .~..~ There are 11 blocks that implement basically these five kinds of neural networks : a) Adaptive Linear Network (ADALINE) 2) Multilayer Layer 102206 with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks, 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) and RBF Networks with Piecewise Linear Dynamic Cell Structure (DCS) algorithm A Simulink example regarding the approximation of a scalar nonlinear function of four variables is included Platform: |
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Author:叶建槐 |
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Description: 利用RBPNN径向基概率神经网络的一个例子，通过该例子可以对RBFNN有个清晰认识-use probabilistic neural network-based one example, through the examples of RBFNN a clear understanding of Platform: |
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Author: |
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Description: there are some newly released Neural Network Example Programs for Character Recognition, which based on Image Processing Toolbox,Neural Network Toolbox in MATLAB, which is quite informative for the beginners in Neural networks applicators-there are some newly released Neural Network Example Programs for Character Recognition, which based on Image Processing Toolbox, Neural Network Toolbox in MATLAB, which is quite informative for the beginners in Neural networks applicators Platform: |
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Author:宏姬 |
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Description: 本文分析小波神经网络的特点重点研究在电力负荷预测中连续小波神经网络与BP神经网络相比具有的优缺点对认识和应用小波神经网络具有重要意义算例表明在网络结构相同的情况下连续小波神经网络比BP神经网络具有更高的预测精度-wavelet analysis of this neural network research focused on the characteristics of the power load forecasting continuous wavelet neural network and BP Neural networks have their advantages and disadvantages compared to the understanding and application of wavelet neural networks is of great significance example shows the network structure with the continuous wavelet neural network than BP neural network has a higher accuracy of prediction Platform: |
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Author:bluebowl |
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Description: 类神经网路,创建LVQ网路对非线性可分离的问题进行分类-neural network, the creation of the Internet LVQ nonlinear separable issues of classification Platform: |
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Author:jack |
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Description: Matlab代码：神经网络的一个实例，修改后可以应用在图像识别的识别部分。-Matlab code : neural network an example, the revised image can be applied to the recognition part. Platform: |
Size: 1024 |
Author:刘晓旭 |
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Description: 每一个训练范例在网络中经过两遍传递计算：一遍向前传播计算，从输入层开始，传递各层并经过处理后，产生一个输出，并得到一个该实际输出和所所需输出之差的差错矢量；一遍向反向传播计算，从输出层至输入层，利用差错矢量对权值进行逐层修改。BP算法有很强的数学基础，戏剧性地扩展了神经网络的使用范围，产生了许多应用成功的实例，对神经网络研究的再次兴起过很大作用。
-Each training example in the network passing through the calculation twice: once to move the spread of computing, from the beginning of input layer, transmission floors and processed to produce an output, and a the actual output and the difference between the desired output error vector again to reverse the spread of computing, from the output layer to the input layer, using error vector values of the right to amend the layers. BP algorithm has a strong mathematical foundation, dramatically expanded the use of neural networks, resulting in a number of successful examples of application of neural network research have a significant role in the rise once again. Platform: |
Size: 1024 |
Author:军军 |
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Description: 模糊神经网络设计，应用神经网络的一个实例 输入为－两输入，输出为－单输出-Fuzzy neural network design, an example of neural network input- two input, output- single output Platform: |
Size: 2048 |
Author:祁峥东 |
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Description: 几个BP神经网络的程序，可以对数据进行分类。改变参数可以输入不同的矩阵数据。-Several BP neural network program, the data can be classified. Changing parameters can enter a different matrix data. Platform: |
Size: 5120 |
Author:anwei |
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Description: 神经网络应用实例，里面有许多好的例子 -Neural network application examples, there are many good examples of neural network application examples, there are many good examples Platform: |
Size: 424960 |
Author:shenyunhuo |
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Search - neural network example