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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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利用随机反向传播网络归类的学习算法。它是LMS算法的自然延伸，也是多层神经网络的有监督训练。-Classify using a backpropagation network with stochastic learning algorithm。
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this program applying artificial intelegence with backPropagation algorithm
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fortran的神经网络训练程序。
Phil Brierley提供
更多信息见 www.philbrierley.com
-Neural Network in Fortran90
!! Multilayer Perceptron trained with
!! the backpropagation learning algorithm
!! coded in Fortran90 by Phil Brierley
!! www.philbrierley.com
!
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This "classic" style of neural network is used for spontaneously generating an algorithm for the analysis of numeric patterns. The goal is to "teach" the network how to analyze a desired set of numeric inputs. For instance, the network might be taugh
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Purpose: This program used for testing source code in
* Chapter 5: Introduction to Neural Networks and the Backpropagation Algorithm
* Book: AI Application Programming
-Purpose: This program used for testing source code in
* Chap
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THIS A BACK PROPAGATION ALGORITHM IN C FROM VALLURU RAO BOOK
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倒傳遞類神經網路,廣泛應用於人工智慧系統-Neural backpropagation is the phenomenon in which the action potential of a neuron creates a voltage spike both at the end of the axon (normal propagation) and back through to the dendritic arbor or dendrites, from which much of
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this to solve the problem of xnor using backpropagation algorithm-this is to solve the problem of xnor using backpropagation algorithm
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XOR_Example % The matrix implementation of the Backpropagation algorithm for two-layer
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深度学习允许由多个处理层组成的计算模型来学习具有多个抽象层次的数据表示。这些方法极大地提高了语音识别、视觉对象识别、目标检测以及药物发现和基因组学等许多领域的最新进展。深度学习发现复杂的结构在大数据集，通过使用反向传播算法来指示一台机器应该如何改变其内部参数，用于计算在每一层的代表性，从上一层的代表。深层卷积网在处理图像、视频、语音和音频方面取得了突破性进展，而递归网络则在文本和语音等连续数据上起到了作用。(Deep learning allows computational models th
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机器学习中神经网络的后向传播算法的相关推导(The derivation of backpropagation algorithm for neural networks in machine learning)
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反向传播ANN的算法实现，里面有简单的data数据demo(Backpropagation ANN algorithm implementation, there is a simple data data demo)
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使用matlab实现的底层cnn算法，包括求卷积，池化，和反向传播等操作(The underlying CNN algorithm implemented using MATLAB, including convolution, pooling, and backpropagation operations)
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