Wavelet_OMP

基于MATLAB_Simulink的系统仿真技术与应用 本书首先介绍MATLAB语言的程序设计的基本内容，在此基础上系约介绍了系统仿真所必要的数值计算方法及MATLAB实现，并以Simu1ink为主要工具介绍了系统仿真方法与技巧，包括连续系统、离散系统、随机输入系统和复数系统的仿真，由浅入深介绍了模块封装技术、电力系统模块集、非线性系统设计模块集、S-函数编写与应用、Stateflow有限状态机、虚拟现实工具箱等中高级使用方法，最后还介绍了半实物仿真技术均实时控制技术。本书可作为一般读者学习和掌握MAlLAB／Simulink语言的教科书，也可作为高校理工科各类专业的本科生和研究生系统仿真类课程的教材和参考书，还可供科技工作者、教师作为学习和应用系统仿真分析技术解决实际问题的参考资料。(This book introduces MATLAB programming language, the basic content, in this based on the simulation system presented about the necessary numerical methods and MATLAB implementation, and Simu1ink introduced the system as the main tool for simulation methods and techniques, including the continuous system , discrete systems, stochastic input system and complex system simulation, Deep introduced module packaging technology, power system block set, set of nonlinear system design module, S-function and application of writing, Stateflow finite state machines, virtual reality tools use of boxes and other senior, finally introduced the loop simulation technology are real-time control technology. )

说明：  配电网潮流计算（40个节点），采用前推后代的方法(distribution network power flow calculation)

LMS自适应滤波器 进行预测 噪声滤除等功能(LMS adaptive filter to predict the noise filtering and other functions)

水平集方法和动态抽象表面，英文版的，需要的话相信不用翻译(level set methods and dynamic implicit surfaces)

《MATLAB神经网络30个案例分析》中的第18个例子，案例18 Elman神经网络的数据预测—电力负荷预测模型研究。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of example, 18 cases of 18 Elman neural network research data to predict- power load forecasting model. Hope to have certain help to everybody! )

matlab编写的有关神经网络的三个小程序，其中包含bp网络，lvq网络和sofm网络(matlab prepared by the neural network of three small program, which includes bp network, lvq networks and sofm Network)

一份简单的FM调制以及解调的matlab程序,对于刚学习通信系统的朋友有用(A simple FM modulation and demodulation matlab program, for a friend just to learn a useful communication system)

this program about image processing

用MATLAB2008A编写的主成成分分析(MATLAB2008A prepared by Principal Component Analysis)

This file contains a summary of what you will find in each of the files that make up your tree application.