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Jingdong book

神经网络实用教程

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Books Computers & Internet Computer Control and Simulation

Jingdong book

神经网络实用教程

Name: 神经网络实用教程
Brand: Jingdong book
SKU: 3118015241
Price: 23.75 USD
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《神经网络实用教程》可作为高校自动化、计算机、材料化工、机械工程、数学、电子工程、信息与信息处理等专业的教材和相关专业工程技术人员的参考书。

Content Description

《神经网络实用教程》基于MATLAB 6.5/7提供的神经网络工具箱，介绍了神经网络常用算法、优化算法及其混合编程实现。全书共分为6章，分别结合实例介绍了人工神经网络概述、实用神经网络模型与学习算法、神经网络算法优化、nnToolKit神经网络工具包、MATLAB混合编程技术、混合编程案例。附录中介绍了2NDN神经网络建模仿真平台。
《神经网络实用教程》可作为高校自动化、计算机、材料化工、机械工程、数学、电子工程、信息与信息处理等专业的教材和相关专业工程技术人员的参考书。

Catalogue

前言
第1章人工神经网络概述
1.1 神经网络的基本概念
1.1.1 生物神经元的结构与功能特点
1.1.2 人工神经元模型
1.1.3 神经网络的结构及工作方式
1.1.4 神经网络的学习

1.2 神经网络的特点及其应用
1.2.1 神经网络的特点
1.2.2 神经网络的应用领域
练习题

第2章实用神经网络模型与学习算法
2.1 MATLAB快速入门
2.1.1 MATLAB界面组成
2.1.2 MATLAB基本运算
2.1.3 MATLAB绘图函数

2.2 感知器神经网络模型与学习算法
2.2.1 单层感知器
2.2.2 单层感知器的学习算法
2.2.3 单层感知器的MATLAB实现
2.2.4 多层感知器

2.3 线性神经网络模型与学习算法
2.3.1 线性神经元网络模型
2.3.2 线性神经网络的学习算法
2.3.3 线性神经网络的MATLAB实现

2.4 BP神经网络模型与学习算法
2.4.1 BP神经网络模型
2.4.2 BP网络的标准学习算法
2.4.3 BP神经网络学习算法的MATLAB实现

2.5 径向基函数神经网络模型与学习算法
2.5.1 RBF神经网络模型
2.5.2 RBF网络的学习算法
2.5.3 RBF网络学习算法的MATLAB实现

2.6 自组织神经网络模型与学习算法
2.6.1 自组织特征映射神经网络结构
2.6.2 自组织特征映射网络的学习算法
2.6.3 自组织网络学习算法的MATLAB实现

2.7 学习向量量化（LVQ）神经网络模型与学习算法
2.7.1 LVQ神经网络结构
2.7.2 LVQ神经网络的学习算法
2.7.3 LVQ神经网络学习算法的MATLAB实现

2.8 Elman神经网络算法模型与学习算法
2.8.1 Elman神经网络结构
2.8.2 Elman神经网络学习算法
2.8.3 Elman神经网络学习算法的MATLAB实现

2.9 Hopfield神经网络模型与学习算法
2.9.1 离散Hopfield神经网络
2.9.2 连续Hopfield神经网络
2.9.3 Hopfield神经网络的MATLAB实现

2.10 Boltzmann神经网络模型与学习算法
2.10.1 Boltzmann机的网络结构
2.10.2 Boltzmann机学习算法

2.11 模糊神经网络
2.11.1 模糊神经网络主要形式
2.11.2 模糊神经网络模型
2.11.3 模糊神经网络学习方法
2.11.4 模糊逻辑MATLAB函数
练习题

第3章神经网络优化方法
3.1 BP网络学习算法的改进
3.1.1 消除样本输入顺序影响的改进算法
3.1.2 附加动量的改进算法
3.1.3 采用自适应调整参数的改进算法
……
第4章 nnToolKit神经网络工具包
第5章 MATLAB混合编程技术
第6章混合编程案例
附录 2NDN神经网络建模仿真工具
参考文献

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