HaarFaceDetect

OFDM技术及其MATLAB模拟，很好的资料哦，可以快速掌握matlab仿真(the study)

说明：  在VC++中调用Matlab引擎的两个例子(In VC++ calling Matlab engines in the two examples)

针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。 (For the signal adaptive the chirplet decomposition of unknown parameters to achieve difficult to literature [1] proposed a new fast algorithm for chirplet decomposition. The algorithm makes use of the secondary phase of the calculated signal function, the conclusion focused on energy distribution curve to tune the frequency of the signal by the peak detection chirplet tune frequency, time center and amplitude estimates then by solving chirp technology to obtain the initial frequency and width is estimated that the simulation results demonstrate the effectiveness of the proposed algorithm.)

说明：  用vc来实现遗传算法，不是matlab哦(vc used genetic algorithms to achieve, not Matlab oh)

反弹的小球程序主要用于模拟小球碰撞后产生反弹的情况。(Rebound ball program mainly used to simulate the small-ball collision resulting from a rebound situation.)

c标准库 参考手册 包括最有用的类和函数(Standard Library Reference)

用matlab编写得一个发泄工具，通过这个可以看出你得英语水平(Using matlab to prepare for a venting tool, through which we can see that you have the standard of English)

Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others. Serious students are directed to the sources listed below for a theoretical description of the algorithm. KF Lee (2) offers an especially good tutorial of how to build a speech recognition system using hidden Markov models.

用matlab实现的视频读取并提取目标背景，对初学者很有用(failed to translate)

去处干涉条纹最有效的频域消除法，非常实用，效果极佳。(supress grid by frequency domain, very practical with high efficency)