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开发实例系列图书：模式识别与智能计算的MATLAB实现

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Jingdong book

开发实例系列图书：模式识别与智能计算的MATLAB实现

Name: 开发实例系列图书：模式识别与智能计算的MATLAB实现
Brand: Jingdong book
SKU: 3118012571
Price: 41.28 USD
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针对各学科数据信息的特点以及科学工作者对信息处理和数据挖掘技术的要求，《开发实例系列图书：模式识别与智能计算的MATLAB实现》既介绍了模式识别和智能计算的基础知识，又较为详细地介绍了现代模式识别和智能计算在科学研究中的应用方法和各算法的MATLAB源程序。本书可以帮助广大的科学工作者掌握模式识别和智能计算方法，并应用于实际的研究中，提高对海量数据信息的处理及挖掘能力，针对性和实用性强，具有较高的理论和实用价值。
本书可作为高等院校计算机工程、信息工程、生物医学工程、智能机器人、工业自动化、地质、水利、化学和环境等专业的研究生、本科生的教材或教学参考书，亦可供有关工程技术人员参考。

Catalogue

第1章绪论
1.1 模式识别的基本概念
1.1.1 模式与模式识别的概念
1.1.2 模式的特征
1.1.3 模式识别系统
1.2 模式识别的主要方法
1.3 模式识别的主要研究内容
1.4 模式识别在科学研究中的应用
1.4.1 化合物的构效分析
1.4.2 谱图解析
1.4.3 材料研究
1.4.4 催化剂研究
1.4.5 机械故障诊断与监测
1.4.6 化学物质源产地判断
1.4.7 疾病的诊断与预测
1.4.8 矿藏勘探
1.4.9 考古及食品工业中的应用

第2章统计模式识别技术
2.1 基于概率统计的贝叶斯分类方法
2.1.1 最小错误率贝叶斯分类
2.1.2 最小风险率贝叶斯分类
2.2 线性分类器
2.2.1 线性判别函数
2.2.2 Fisher线性判别函数
2.2.3 感知器算法
2.3 非线性分类器
2.3.1 分段线性判别函数
2.3.2 近邻法
2.3.3 势函数法
2.3.4 SIMCA方法
2.4 聚类分析
2.4.1 模式相似度
2.4.2 聚类准则
2.4.3 层次聚类法
2.4.4 动态聚类法
2.4.5 决策树分类器
2.5 统计模式识别在科学研究中的应用

第3章人工神经网络及模式识别
3.1 人工神经网络的基本概念
3.1.1 人工神经元
3.1.2 传递函数
3.1.3 人工神经网络分类和特点
3.2 BP人工神经网络
3.2.1 BP人工神经网络学习算法
3.2.2 BP人工神经网络MATLAB实现
3.3 径向基函数神经网络RBF
3.3.1 RBF的结构与学习算法
3.3.2 RBF的MATLAB实现
3.4 自组织竞争人工神经网络
3.4.1 自组织竞争人工神经网络的基本概念
3.4.2 自组织竞争神经网络的学习算法
3.4.3 自组织竞争网络的MATLAB实现
3.5 对向传播神经网络CPN
3.5.1 CPN的基本概念
3.5.2 CPN网络的学习算法
3.6 反馈型神经网络Hopfield
3.6.1 Hopfield网络的基本概念
3.6.2 Hopfield网络的学习算法
3.6.3 Hopfield网络的MATLAB实现
3.7 人工神经网络技术在科学研究中的应用

第4章模糊系统理论及模式识别
4.1 模糊系统理论基础
4.1.1 模糊集合
4.1.2 模糊关系
4.1.3 模糊变换与模糊综合评判
4.1.4 Ifthen规则
4.1.5 模糊推理
4.2 模糊模式识别的基本方法
4.2.1 最大隶属度原则
4.2.2 择近原则
4.2.3 模糊聚类分析
……
第5章核函数方法及应用
第6章支持向量机及其模式识别
第7章可拓学及其模式识别
第8章粗糙集理论及其模式识别
第9章遗传算法及模式识别
第10章蚁群算法及其模式识别
第11章粒子群算法及其模式识别
第12章可视化模式识别技术
第13章灰色系统方法及应用
第14章模式识别的特征及确定
参考文献

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