最经典的图像置乱-imageEncryption-master

M=8,fc=6/T时的8个波形，和M=4的PSK通信系统的Monte Carlo仿真(M = 8, fc = 6/T at the time of 8 waveforms, and M = 4 of PSK communication systems Monte Carlo simulation)

给出了MATLAB语言实现IIR滤波器的实现，源文件中还有原理方法(MATLAB language are given the realization of IIR filters, there is the principle source document method)

MATLAB学习与应用，便于同学掌握其相关功能，实现在学习中熟练应用(Learning and application of MATLAB to facilitate the students to master their related functions, to achieve proficiency in the application of learning)

在ＭＡＴＬＡＢ中非平稳信号的调用函数，生成以Ｔ０为中心的双边指数调幅信号(MATLAB Central Africa in a smooth signal transfer function, T0 generation to the center of the bilateral index AM signal)

次代码描述怎样实现用matlab仿真一个雷达上常用的信号——线性调频脉冲信号。(This code is to describe how to generate the use of MATLAB simulation of a radar signals commonly used-- linear frequency modulation pulse（LFM） signal.)

The onset of the T wave is the beginning point of the T wave, it s the first negative or null sample preceeding the T peak. The offset of the T wave is the ending point of the T wave, it s the first positive or null sample following the T peak.

此为基于MATLAB平台确定指纹图像中心点的算法(This is based on MATLAB, the algorithm to determine the center of the fingerprint image)

System will automatically delete the directory of debug and release, so please do not put files on these two directory.

The REMUS simulator program was written using MATLAB. The first program, REMUSSIM.m,loads the vehicle initial conditions and tracks the vehicle state. The second program, REMUS.m,calculates the new vehicle accelerations based on the vehicle state and control inputs.

最经典AdaBoost实现，适合初学，有大量详细的注释，容易理解(This a classic AdaBoost implementation, in one single file with easy understandable code. The function consist of two parts a simple weak classifier and a boosting part: The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1 The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier" 。)