wavRecordAndSuperimpose

曹希仁的Stochastic Learning and Optimization课件，绝对经典(The Stochastic Learning and Optimization Xiren Cao courseware, absolute classic)

一个简单的电梯模型，使用matlab软件编写的程序仿真出电梯模型(A simple elevator model, the use of simulation matlab software programs written out of the elevator model)

对接收信号进行分离是信号处理过程中经常用到的，然而在完全不知道接受信号先验知识的情况下进行分离就是所谓的盲源分离，此程序就是重多盲源分离算法中重要的一种快速独立分量分析盲源分离算法——FASTICA(Separation of the received signal is the signal processing is often used, but do not know to accept in full prior knowledge of the signal to separate the case of the so-called blind source separation, this procedure is more emphasis on blind source separation algorithm is an important one kinds of fast independent component analysis algorithm for blind source separation- FASTICA)

说明：  高等光学仿真（matlab版）-光波导、激光书中部分程序(Higher optical simulation (matlab)- waveguide, the laser part of the program in the book)

This text provide good training for general use of Matlab and numerical programing application of Matlab

Image hiding - Steganography This program to hide a text file in 24-bit bitmap image

matlab code for beging cc motor...

指纹识别系统，调试成功后的源码，带有图片，matlab 7.0 直接运行(Fingerprint identification system, source code debugging success, with pictures directly run matlab 7.0)

基于matlab的数字计算资料，既有程序也有案例，最新最全。(This book is a survey of the numerical methods that are common to undergraduate courses in Science, Computing, Engineering and Technology. The aim is to present sufficient methods to facilitate the numerical analysis of mathematical models likely to be encountered in practice. Examples of such models include the linear equations describing the stress on girders, bridges and other civil engineering structures, the differential equations of chemical and thermal reactions, and the inferences to be drawn from observed data.)

最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數，以類比所需理想濾波器的自適應濾波器，其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正，是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)