Optimal problem solver

在matlab开发环境下实现m-shift图像目标跟踪算法，其中还有一篇比较好的参照论文(Development environment in the matlab m-shift image to achieve target tracking algorithm, of which there are a good reference paper)

说明：  运用遗传算法进行多元多峰函数优化，多目标问题优化！有案例！可以运行！(using Genetic Algorithm to test multi-peak function and multi-objective function.)

一种全面进行信号分类与绘图的程序代码，对离散信号的处理很强大。(signal analysis)

数字信号处理，包括：各种现有信号及随机信号的输入，从文件读取数据的输入，各种滤波器的实现，傅里叶变换等，傅里叶反变换等，谱分析，利用图形界面形式编写，简单且可视化强，便于理解。(Digital Signal Matlab)

自然激励下建筑结构的模态参数识别，首先通过自然激励技术（next）得到结构的自由响应，然后由自回归滑动平均（arma）方法识别模态参数。(natural incentive structures under the modal parameter identification, First through natural incentive Technology (next) to be free to respond to the structure, then autoregressive moving average (arma) identified modal parameters.)

Fountain code for compression

井下通信时的链路预算，包括误码率和信道容量的仿真。(Underground communication link budget, including the BER and channel capacity in the simulation.)

运动目标的检测是视频处理过程中后续跟踪技术的基础,其检测结果的好坏直接关系到能否跟踪到运动目标及跟踪准确度问题。运动目标的检测就是从机器视觉系统获取的序列图像中把前景,运动,目标分割提取出来的过程。本文描述了机器视觉中运动目标检测的主要方法?介绍了其中背景减除法的几种典型算法的原理、特点、背景差分法的基本流程?主要包括四个步骤为,预处理、背景建模、目标检测、后处理。然后在matlab环境下运用背景减除算法完成了视频中运动目标的检测,并对检测结果图像进一步处理.(Moving target detection is a follow up video processing technology based on the test results is directly related to the ability to track moving targets and tracking accuracy. Moving target detection prospects, movement, object segmentation extracted from the sequence of images acquired by the machine vision system. This paper describes the main method of moving target detection machine vision ? introduced the principle of which several typical algorithms for background subtraction method, the basic flow characteristics, background difference method ? mainly includes four steps, preprocessing, background modeling target detection, post-processing. Use background subtraction algorithm in Matlab environment complete video moving target detection, and detection results of images for further processing.)

基于面阵的信号方位角与频率的联合估计，采用MUSIC算法(Based on the planar array of signal azimuth and frequency of joint estimation using MUSIC algorithm)

The function applies the Madsen method for Doppler Centroid estimation. The input are: 1) the raw data, the parameter of the distance between samples in azimuth to be correlated and the PRF (Pulse repetition frequency)