segymat-1.08

自适应滤波器LMS算法的改进后的源程序的MATLAB程序(LMS adaptive filter algorithm improved source)

该代码为matlab代码，其内容是基于最大信噪比的盲源分离算法。可将该算法用于语音信号、图像信号的处理中。(The code for the matlab code, its content is based on the maximum SNR of the blind source separation algorithm. The algorithm can be used for voice signals, image signal processing.)

说明：  gmsk调制解调程序，利用matlab进行仿真，通信类设计可用(gmsk modulation and demodulation process, using matlab simulation, Communications design available)

如果阵元间距小于半波长，则阵元间会产生耦合。如果阵元间距大于半波长，则阵列上会现多余的旁瓣，从而降低天线阵列的性能。而当阵列间距选取为半波长时，所估测出的效果最优。(If the array element spacing is less than half wavelength, it will produce coupling between array elements. If the array element spacing is greater than half wavelength, the array will now be extra sidelobes, thus reducing the performance of the antenna array. When the array spacing is half wavelength selection, the best estimate the effect.)

说明：  In computer science, differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Such methods are commonly known as metaheuristics as they make few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions. However, metaheuristics such as DE do not guarantee an optimal solution is ever found.

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. )

用matlab软件仿真了从卷积码编码，QPSK调制，AWGN信道，QPSK解调，以及Viterbi译码。(Using Matlab Simulate from the coding of convolutional code，Qpsk modulation ，AWGN channel ，Qpsk demodulation and Viterbi decoding。)

基于matlab的画出一个不完整的椭圆，结果完美。只要稍作修改可以出来任意要求范围的不完整椭圆。(Matlab to draw the ellipse )

数字信号处理应用设计了各种滤波器，能够完成信号的处理(The digital signal processing applications design of a variety of filters, to complete the processing of the signal)

matla编程指南，常见错误，适用于matlab初学者和中级学者(Matla Programming Guide, Common mistakes)