qiujizhi

this mfile is riten in matlab and is related to mirtoolbox

本文档介绍了关于信道仿真的一些程序代码和一些仿真结果，并对各种信道仿真结果做了比较和分析(This document describes a number of channel simulation program code and some simulation results, and a variety of channel simulation result of the comparison and analysis)

遗传算法工具箱，英国谢菲尔德大学编制，可以根据个人需要进行 修改(Genetic Algorithm Toolbox, University of Sheffield, UK establishment, can be modified according to individual needs)

和自回归模型一起写的小波模型，里面用到了自回归，自回归模型已上传(Since the regression model and the wavelet model with writing, which used the autoregressive, autoregressive models have been uploaded)

parzen窗算法，适合于初学者。包括paren的matlab源代码，以及测试文件。(Parzen window algorithm)

正弦函数的离散傅里叶变换，输出傅里叶变换系数(Discrete Fourier sine transform, Fourier transform coefficients output)

This file is implementing a bluetooth system which is equipped with frequency hopping method, this method is used for system protection against jamming, This is a matlab simulink file.

微分方程（这里指的是常微分方程）指含有一次、二次、乃至高次微分未知数的方程。是解决偏微分方程、数理方程的基础。有许多特殊函数，都是为了无法得出多项函数或超越函数型式的解析解的微分方程而定义出来。这些特殊函数之所以重要，是因为它们描述了自然界中的某些现象，例如，电子的活动、鼓皮的振动、钟摆的摆动等等。(Differential equations (in this case is the ordinary differential equation) means containing one, two, and even high-differential equations unknowns. Is to solve the partial differential equations, mathematical equations based. There are many special functions, are not drawn to a number of functions or functions beyond the type of analytical solution of differential equations which define them. These special functions are important because they describe the nature of certain phenomena, for example, electronic activities, drum skin vibrations, pendulum swing, and so on)

自己用的时域特征提取方式，包含均值，均方根值，歪度，峭度，峰值指标，阈值裕值指标，峭度指标等，然后用RBF做聚类(The method of feature extraction in time domain includes mean value, root mean square value, skewness, kurtosis, peak value index, threshold margin index, kurtosis index, etc. Then RBF is used for clustering.)

说明：  削减平均恒虚警(TM-CFAR)检测器和双门限（double threshold）检测器，用于强噪声环境下的多目标检测(detectors based on the trimmed mean technique and double threshold technique.)