channel_case3

Principal Component Analysis on the FERET Dataset

该书包含全面的MATLAB函数及其使用方法，可方便查询使用(The book contains a comprehensive MATLAB functions and their use can be easier to find)

本gatbx遗传算法工具箱是在原设菲尔德大学gatbx工具箱基础上的改进，扩展了原gabtx功能，将原始的基于命令式的mpga.m及sga.m文件封装成函数形式，使用更简单易懂，适合初学者或一些只要求用遗传算法解决实际问题而不需深究遗传算法本身的同学。(The gatbx genetic algorithm toolbox in the original design the Rumsfeld the University gatbx Toolbox based on the improvements, extended the original gabtx function, the functional form of the original package based the command-mpga.m sga.m file, more simple to use and easy to understand.suitable for beginners or some only require genetic algorithm to solve practical problems and do not need to get to the bottom of the genetic algorithm itself classmates.)

The main idea behind this book, and the incentive for writing it, is that strong connections exist between adaptive filtering and signal analysis, to the extent that it is not realistic—at least from an engineering point of view—to separate them. In order to understand adaptive filters well enough to design them properly and apply them successfully, a certain amount of knowledge of the analysis of the signals involved is indispensable. Conversely, several major analysis techniques become really efficient and useful in products only when they are designed and implemented in an adaptive fashion. This book is dedicated to the intricate relationships between these two areas. Moreover, this approach can lead to new ideas and new techniques in either field.

包含九种图像评价函数，对图像进行清晰度判断并对比各种方法的时效(Evaluation function contains nine images, the image clarity and compared various methods of aging)

this program apply the kohonen method to classify some data.

解非线性方程,方程首先要给定两个初始值，并且函数在这两个值的函数值的乘积小于0(solve equantions that are not linear)

针对案例数据，用matlab软件对数据进行极差法归一化处理；并使用主成分分析法分析选定成分的特征值贡献率，从而为进行下一步数据分析做一些准备。(According to the case data, the data is normalized by range method with MATLAB software, and the contribution rate of the selected components is analyzed by principal component analysis, so as to make some preparations for the next step of data analysis.)

BP学习算法应用——模式分类 应用动量BP学习算法对UCI提供的经典数据库——鸢尾属植物数据库进行分类，速度快，精度高。iris.arff为数据库文件，可用Weka数据挖掘软件打开。Iris.csv为源代码读取的数据文件，通过Weka软件转换得到。 将源文件Iris_classify.m和Iris.csv文件放入matlab的work文件夹中直接运行即可。(BP learning algorithm applications- the application of pattern classification momentum BP learning algorithm to provide a classic UCI database- iris database classification, high speed and accuracy. iris.arff for the database file that can be used to open Weka data mining software. Iris.csv for the source code to read the data files have been converted through Weka software. Iris_classify.m the source document and document Iris.csv Add matlab folder of work can be directly run.)

lsqr.m 基于QR正交分解的最小二乘法......(lsqr.m QRLS............................)