metrix_vsnr

是一个 报童的发报问题的程序 你看了会受益滴..(The transmitter is a newsboy problem will benefit from the program drops you read ..)

首先用雷克子波合成正演地震记录，得到较好的记录结果，然后用此结果进行F-K的波长延拓，得到偏移结果。(The first wave of synthetic forward with Leike Zi seismic records, the records get better results, then use the results of FK wavelength extension, to be offset results.)

任意长度的rs码编译码，编译通过，易于扩展学习(s codes and decoding of any length, compile, easy to extend learning)

说明：  matlab编写的leader_follower[数据挖掘]分类算法。(Matlab leader_follower prepared by the [data mining] classification algorithm.)

Function for power quality disturbances (Notch), lets customer to choose parameters

implementation of butterworth high pass filter

本仿真是基于matlab的capon波束形成，包含3个仿真(The simulation is based on Matlab capon beamforming, contains three simulation)

这是2014年在自然杂志上发表的密度峰聚类的代码(This is 2014 in Nature magazine published the density peak clustering code )

说明：  用S函数编写的量化器 量化步长为非线性 即 量化步长可调 (Prepared by S function to quantify the quantizer step size for the non-linear quantization step size that is adjustable)

说明：  这本书描述了MATLAB遗传算法的特性和直接搜索工具箱,编程原理和使用方法。这本书分为九章。第一章到第四章介绍了遗传算法的基本知识,包括遗传算法的基本原理、编码、选择、交叉、变异、适应度函数、控制参数、约束处理,模式定理,改进遗传算法早熟收敛问题及其预防等等。第五章到第七章介绍MATLAB遗传算法工具箱英格兰谢菲尔德谢菲尔德大学,和使用方法,如何编写这个函数的一个示例使用遗传算法工具箱解决实际优化问题的MATLAB程序。(The book describes the characteristics of MATLAB genetic algorithm and direct search toolbox, programming principle and method of use. The book is divided into nine chapters. The first chapter to the fourth chapter introduces the basic knowledge of the genetic algorithm, including the basic principle of genetic algorithm, coding, selection, crossover, mutation, fitness function, control parameters, constraints, processing, schema theorem, improved genetic algorithm premature convergence problem and its prevention and so on. Fifth chapter to the seventh chapter introduces MATLAB genetic algorithm toolbox Sheffield in England at the university of Sheffield, and use a method, an example of how to write this function using MATLAB genetic algorithm toolbox to solve practical optimization problem.)