61046606ABCNNTrain

用Matlab实现图像的整数小波变换和逆变换，对行和列各做一次，采用最简单的S小波，它是Haar变换的整数形式。此程序代码为逆程序代码(Using Matlab for image wavelet transform and inverse integer transform, the rows and columns to do once the most simple and S-wavelet, which is the integer Haar transform. This program code against the code)

运用matlab/simulink创建一单机无穷大电力系统暂态稳定性分析(Transient stabilty analysis of one-machine infinite bus power system)

matlab例程100，可以作为学习matlab和研究时的工具书，方便查阅；(matlab routine 100, can be used as study and research matlab book at the time of instrument for easy access )

说明：  可进行位置识别,通过声源的波束形成,可知道其相关信息.再加上(can identify the location, source, a beam forming, know relevant information. Plus )

This is the information about wavelett transform use in matlab

压缩感知里面的稀疏重建问题，在原来MP的算法的基础上，提出了分块的思想，即将原子库分块后，测试算法的性能。(Compressive sensing is refered as the block sparse algorithm is described,that is based on the original MP algorithm,and the atom libruary is divided into blocks ,and the performance is testified.)

用卡尔曼滤波器实现目标追踪，利用蒙特卡洛的方法对跟踪滤波器进行仿真分析，次数为1000次 (Kalman filter to achieve target tracking, using the Monte Carlo method of tracking filter simulation analysis, the number is 1000 times)

关于matlab电力系统暂态稳定的短路计算的一些源程序同时是有关优化的源程序(Matlab power system transient stability of short-circuit calculations for some source code is also optimized source)

标准粒子群算法的实现思想基本按照粒子群算法(2) 标准的粒子群算法的讲述实现。主要分为3个函数。第一个函数为粒子群初始化函数 InitSwarm(SwarmSize......AdaptFunc)其主要作用是初始化粒子群的粒子，并设定粒子的速度、位置在一定的范围内。本函数所采用的数据结构如下所示： 表ParSwarm记录的是粒子的位置、速度与当前的适应度值，我们用W来表示位置，用V来代表速度，用F来代表当前的适应度值。在这里我们假设粒子个数为N，每个粒子的维数为D。(His thought of the implementation of the standard particle swarm algorithm according to the particle swarm algorithm (2)- the standard particle swarm algorithm about implementation. Mainly divided into three functions. The first function of particle swarm initialization function InitSwarm (SwarmSize... AdaptFunc), its main function is to initialize particle swarm particle, and set the particle s velocity, position in a certain range. The function of data structure is as follows: ParSwarm record table is the particle s position, speed and the current fitness value, we use W to represent the position, represented speed with a V, to represent the current fitness value with F. Here we assume that the number of particles N, each particle dimension for D.)

Finite memory least square method