MATLABapplication

gmsk modulation of numerical data generated by a random source, the output of the modulator give two signals, the first is gmsk signal and the other is gaussien frequency pulse shape

同步发电机，用于仿真用，6.5以上可打开(Synchronous generator for the simulation used to open more than 6.5)

matlab实现的函数y=sinx的拟合程序，使用bp网络构造的算法，很简单很好用，已经实现结果(matlab a function of the realization of y = sinx fitting procedures, the use of the algorithm bp network structure is very simple and very good, and the results have been achieved)

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.

基于LS和MMSE算法实现信道估计，采用块序列(Based on LS and MMSE algorithm, realized channel estimation )

Matlab code for clustering algorithm.

间接广义最小方差控制实例，可用于参数未知的情况进行预测控制(indirect Gmvc)

matlab常见方程求根常用方法打包，可以供初学者使用(The matlab common equation Root common method of packaging, for beginners)

人工智能课的一些作业，对选人工智能这门课的有很大帮助(Artificial Intelligence course some of the work on artificial intelligence selection of great help for this class)

matlab函数scaleif，用于改变度量，详见英文描述( function sim = scaleif(im, newMin, newMax, oldMin, oldMax) Scales an image such that its lowest value attains newMin and it highest value attains newMax. OldMin and oldMax are not necessary but are useful when you don t want to use the true min or max value.)