粒子群算法工具箱及代码

Tracking a moving object through several frames, provided changes from frame to frame are on the order of +-(10 + "X Range") pixels in the X direction and +-(10 + "Y Range") in the Y direction is done automatically because of a relatively large area of exploration during the search for an optimal (new) position for a particular control point and a very strong force exerted by large values of the image gradient.(Tracking a moving object through several frames, provided changes from frame to frame are on the order of+-(10+ "X Range") pixels in the X direction and+-(10+ "Y Range") in the Y direction is done automatically because of a relatively large area of exploration during the search for an optimal (new) position for a particular control point and a very strong force exerted by large values of the image gradient.)

对光学系统中常用的正弦振幅型透射光栅进行了仿真，仿真结果有衍射图案和光强沿x轴方向的曲线。(Of the optical system used in the amplitude of the sinusoidal transmission grating-based simulation, simulation results diffraction patterns and light intensity along the x-axis direction of the curve.)

为工程设计人员提供帮助，同时为其它设计提供思路(guide)

说明：  本源程序为 语谱图源程序 可以清楚的得到语谱图(The source spectra for the source language can clearly be Spectrogram)

基于sobel算子的简单车牌识别提取，算法简单 (Sobel operator based on the simple extraction of license plate recognition algorithm is simple)

最优阵列处理随书程序，最全版本,包含课后习题程序(matlab code of optimum array processing)

Handbook of Practical MATLAB® for Engineers Practical MATLAB® Basics for Engineers Practical MATLAB® Applications for Engineers

说明：  这个资料里门有很多关于matlab编程的资料，是个不错的资料(This information inside the door there are a lot of information on the matlab programming is a good information)

AITKEN S INTERPOLATION Aitken s procedure yields systematically and successively better interpolation polynomials corresponding to successively higher order truncation of Newton s divided difference formula. Given a set of x and corresponding f(x), estimate f1(x1) f1= aitkenInterp(x,f,x1) f = corresponding function of x f1= corresponding function of x1

说明：  压缩感知的例子。重建是用在稀疏域上求最小零范数的方法。首先把零范数凸松弛为一范数，然后变成线性规划问题，从而求得最优解。(An example of the compressive sensing. Its reconstruction is based on L0-norm minimization.)