ACF_exam2

说明：  这是一个wiener滤波程序，对语音信号滤波。里面有详细的word文档说明(This is a wiener filtering process to filter the speech signal. There are detailed notes word document)

自己做的： （一）用双线性变换法设计并用实验系统实现一个三阶的契比雪夫Ⅰ型低通数字滤波器，其采样频率Fs =8KHz，1DB通带边界频率为fp=2KHz。 （二）用双线性变换法设计并用实验系统实现一个三阶的契比雪夫Ⅱ型高通数字滤波器，其采样频率Fs =16KHz，阻带边界频率为fst =4KHz，As=20dB。 ((A) design using the bilinear transformation method and the experimental system of a third-order Chebyshev low-pass type Ⅰ digital filter, the sampling frequency Fs = 8KHz, 1DB passband boundary frequency is fp = 2KHz. (B) Bilinear transformation method used to design and use of the experimental system of a third-order Chebyshev type Ⅱ high-pass digital filter, the sampling frequency Fs = 16KHz, stopband boundary frequency fst = 4KHz, As = 20dB.)

this is source code in matlab and the code is about how to read traffic ligth sign

实现FIR系统中的最小均方误差自适应滤波算法（LMS）,并通过误差曲面研究其性能。(FIR system in the minimum mean square error adaptive filtering algorithm (LMS), and study its performance through the error surface.)

使用matlab的simulink工具箱，对平面二连杆机构进行动态仿真(Matlab dynamic simulation of Two-linkage mechanism)

finger recognition in matlab

This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. (This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. )

说明：  这本书用matlab仿真了数字通信原理中的各部分，很有参考价值(This book matlab simulation of digital communication with the various parts of the principle, a good reference)

matched filter bound implementation in matlab for a certain channel responses in a noisy channel

FCM聚类算法 已经通过调试，可以直接使用。(FCM clustering algorithm has been through debugging, can be used directly.)