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自适应(Adaptive)神经网络源程序
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
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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) A
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* Lightweight backpropagation neural network.
* This a lightweight library implementating a neural network for use
* in C and C++ programs. It is intended for use in applications that
* just happen to need a simply neural network and do not
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基本上实现这些类型的神经网络：
自适应线性网络（ADALINE）
多层多层感知器网络
广义径向基函数网络
动态细胞结构（DCS）网络与高斯或圆锥形的基础功能-There are blocks that implement basically these kinds of neural networks:
Adaptive Linear Networks (ADALINE)
Multilayer Layer Perceptron Networks
Generalized
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fisher线性分类，多层感知器非线性分类，K-Means聚类-Fisher linear classification, multilayer perceptron linear classifiers, K-Means Clustering
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一个用MATLAB实现的多层感知器 MATLAB multilayer perceptron-A multilayer perceptron MATLAB MATLAB multilayer perceptron
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MLP multilayer neural network
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基于halcon，运用多层感知的分类器字符识别，和颜色识别、(Based on Halcon, multilayer perceptron classifier is used for character recognition and color recognition,)
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一个用MATLAB实现的多层感知器 MATLAB multilayer perceptron(A multilayer perceptron MATLAB MATLAB multilayer perceptron)
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Recurrent Multilayer perceptron
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Extreme Learning Machine for Multilayer Perceptron
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人工神经网络 /多层感知器 归一化 神经网络的30个案例(artificial neural network/Multilayer perceptron normalization)
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深度学习的概念源于人工神经网络的研究。含多隐层的多层感知器就是一种深度学习结构。深度学习通过组合低层特征形成更加抽象的高层表示属性类别或特征，以发现数据的分布式特征表示。(The concept of deep learning stems from the study of artificial neural networks. A multilayer perceptron with a hidden layer is a depth learning structure. Depth le
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BP神经网络算法实现例子，多层感知机，对非线性函数逼近(neural network and Multilayer perceptron)
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深度学习的概念源于人工神经网络的研究。含多隐层的多层感知器就是一种深度学习结构。深度学习通过组合低层特征形成更加抽象的高层表示属性类别或特征，以发现数据的分布式特征表示(The concept of deep learning stems from the study of artificial neural networks. A multilayer perceptron with a hidden layer is a depth learning structure.)
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这个例子是感知器人工神经网络的异或门实现，这是多层感知器神经网络的一个典型例子。(This example is the XOR gate implementation of perceptron artificial neural network, that is a classic example of a multilayer perceptron neural network.)
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多层感知机能够学习并预测神经网络结构等，对故障程度进行预测(The multilayer perceptron can learn and predict the neural network structure and so on, to predict the degree of failure.)
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应用人工神经网络的建模方法，采用多层感知器的模型结构，利用自适应学习速率的BP学习算法(The application of artificial neural network algorithm and the model structure of multilayer perceptron)
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