colea_1741-(1)

basic4ppc最新帮助，参考书籍，可以快速开发PPC软件(basic4ppc the latest help, reference books, you can quickly develop PPC Software)

常用分形算法的mablab实现，包括递归算法、L系统算法、IFS迭代和逃逸时间算法(Fractal algorithm mablab commonly realized, including recursive algorithm, L system algorithm, IFS iteration and escape time algorithm)

PSCAD仿真模型，可以用来研究SSO问题。(The PSCAD simulation model can be used to study SSO problems.)

用MATLAB语言实现BCH的编码和译码(BCHcode and decode)

相控阵列天线方向图的matlab实现，来自学报(Phased array antenna pattern matlab realize, from University)

一个基于信息最大化生成显著图的程序对于彩色或红外图像都有很好的效果(Based information maximization generate significant chart program has a good color or infrared image effect)

The channel modeling work package WP1 of IST-WINNER project provided a Matlab implementation of the WINNER Phase II Model (referred as WIM this onward). The main purpose of the WIM channel models is to generate a radio channel realisations for a link and system level simulations. The implementation is based on the earlier implementations of WINNER II interim model [6], WINNER I (interim) model [3], 3GPP/3GPP2 Spatial Channel Model (SCM) [4] and SCM(E) Extension models. For details concerning the WIM model, please refer to [1]. This document describes the SW implementation structure of WIM, its input/output interface and its functionality. Channel model scenarios and parameters are modified to correspond to IMT.EVAL [7] channel model.

A simple example showing how to track an object with particle filter. Likelihood is based on Bhattacharya distance of color histogram.

这是2009年huang在EMD基础上改进的算法EEMD的matlab代码！(This is the huang in 2009 based on the improved EMD algorithm EEMD matlab code!)

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)