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小波神经网络的源程序: 1.构造的非线性函数: 位于nninit_test.m 2.直接用WNN逼近非线性:Wnn_test.m, (内部调用小波函数) 3.遗传算法优化后逼近 :GA_Wnn_test.m (内部调用遗传算法的,初始化,适应度,解码函数)-genetic algorithm optimization WNN source : 1. Construction of the nonlinear function : nninit_test.m at 2. WNN directly with nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions) (Wavelet neural network source code: 1. Construction of the nonlinear function: at nninit_test.m 2. Wnn the direct use of nonlinear approximation: Wnn_test.m, (internal call wavelet function) 3. Genetic algorithm optimized approximation: GA_Wnn_test. m (internal call genetic algorithms, initialization, fitness, decoding function)-genetic algorithm optimization WNN source: 1. Construction of the nonlinear function: nninit_test.m at 2. WNN directly with nonlinear approximation: Wnn_test.m. ( internal called wavelet function) 3. Genetic Algorithm optimization approach: GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions))

说明：  function [ret,x0,str,ts,xts]=s3(t,x,u,flag) s3 is the M-file description of the SIMULINK system named s3. The block-diagram can be displayed by typing: s3. SYS=s3(T,X,U,FLAG) returns depending on FLAG certain system values given time point, T, current state vector, X, and input vector, U. FLAG is used to indicate the type of output to be returned in SYS.

计算多速滤波器以及其优化算法和加快速率的提高(this program can help you improve the filter )

本程序可以显示常见激光模式分布图，如TE00，TE01,TE10,TE22等，有助于对激光横模的理解！(This program is to help students to understand to the laser mode )

brushless dc drive motors simulations

sampling of rect signal

这是一本关于光纤通信系统设计的书，以optisystem为基础对光通信的仿真实验。(This is a book about the fiber optic communication system design to optisystem basis for the simulation of optical communication.)

说明：  基于长记性特征的时间序列预测模型，很好用，准确度优于普通神经网络，我自己一直在用(Characteristics based on long memory time series forecasting model, the good, the accuracy is better than an ordinary neural network, I have been using)

小波分析，基于DWT的故障信号特征提取，可以画出条形图，多层分解(Wavelet analysis, DWT-based feature extraction of fault signal can draw bar charts, multi-decomposition)

simulink的仿真有两个阶段：一个为初始化，这个阶段主要是设置一些参数，像系统的输入输出个数、状态初值、采样时间等；第二个阶段就是运行阶段，这个 阶段里要进行计算输出、更新离散状态、计算连续状态等等，这个阶段需要反复运行，直至结束。(simulink simulation has two phases: one for initialization, this stage is mainly to set some parameters, such as the number of input and output system, initial state, the sampling time second stage is the operational phase, the Stages to calculate the output, update the discrete state, continuous calculation of the state, etc., this stage requires repeated runs to the end.)