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ai's Introduction

计算智能

第一章

第二章 神经网络

(1)BP神经网络

激活函数

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(1)人工神经网络(ANN)

前馈型神经网络

主要是函数映射,用于模式识别和函数逼近

反馈型神经网络

按对能量函数的所有极小点的利用情况,可将反馈型神经网络分两类:

一类是能量函数的所有极小点都起作用,主要用作各种联想存储器;

另一类只利用全局极小点,主要用于求解优化问题。

神经网络的学习

学习方法

有监督学习

无监督学习

再励学习

学习规则

Hebb学习规则:“当某一突触(连接)两端的神经元同步激活(同为激活或同为抑制)时,该连接的强度应为增强,反之应减弱”。

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Delta学习规则

梯度下降学习规则

Kohonen学习规则

后向传播学习规则

概率式学习规则

竞争式学习规则

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(2)Hopfield神经网络

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