four-fast-Fourier-transform

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.

很好的一篇论文，内容讲解的很透彻啊，在我的工程项目中可是帮了大忙了(Very good paper, the content on a very thorough ah, in my project but of great help the)

说明：  自适应PSD神经元控制,用于伺服电机的调速度,比单神经元有跟好的鲁帮性(adaptive neural control for the servo-motor speed, a single neuron with good Lu hand)

伪随机序列发生及检测程序，适用于卫星通信(Pseudo-random sequence and testing procedures applicable to satellite communications)

this a code about CDMA

Cichocki教授的一些关于盲源分离的研究成果。内容主要在于盲源的提取。是一部分很好的内容。(Cichocki D.R，blind source separation,blind source extraction)

稀疏人脸识别,来至论文Robust Face Recognition via Sparse Representation(Robust Face Recognition via Sparse Representation)

IDMA matlab file algorithm

Guassian Hidden markov model

La señ al x(t) = 2 cos(11.200πt) + 2cos (10.000 πt) cos (1.000 πt) se suma a una señ al de ruido blanco (coloreado) gausiano de banda limitada con media igual a cero y con una densidad espectral de potencia de 1 µ w/Hz hasta una frecuencia de 15.000 Hz y cero a frecuencias mayores.