802.11a_OFDM

根据课本《现代数字信号处理及其应用》例题编写的music波束形成算法的matlab仿真(music beamforming)

利用Matlab软件工具，对简单的植被形态进行模拟，模拟结果生动逼真。首先，迭代产生一系列字符串；其次，根据将L系统与图形联系起来，采用龟形的概念赋予每个字符特定的图形含义；最后，读取字符并画图，根据读取到的字符通过Matlab实现相应的操作。(According to L system and iterated algorithm, shape of trees were simulated with matlab functions and programs and the fractal trees’ configurations were natural and living. First, we use iteration to produce a series of string. Then, connecting the L system with graphs, we use the theory of turtles to give each character a specific meaning. Finally, read the string and draw pictures with the matlab. )

A Particle Filter Based Algorithm for State Estimation of Dim Moving Point Targets in IR Image Sequence

说明：  该程序用于大地反算，参考于武汉大学测绘学院出版的大地测量学基础（第二版）(The inverse procedure for the earth, the reference in the School of Surveying and Mapping, Wuhan University, published the basis of Geodesy (second edition))

用Matlab程序求解pde问题，同时显示解的图形(Solving pde problems with the Matlab program, also shows a graphical solution)

BP神经网络详解与实例，包括多种操作实例与演示说明(BP neural network Xiangjie instructions and examples, including a variety of operating instance with demo)

Project for Cal Poly Pomona ARO 401 course.

扩频通信基础框架，基于matlab扩频通信基础框架，基于matlab(Spread spectrum communications infrastructure framework based on matlabSpread spectrum communications infrastructure framework based on matlab)

经典的香农采样定理认为,为了不失真地恢复模拟信号,采样频率应该不小于奈奎斯特频率(即模拟信号 频谱中的最高频率)的两倍.但是其中除了利用到信号是有限带宽的假设外,没利用任何的其它先验信息.采集到 的数据存在很大程度的冗余.Donoho等人提出的压缩感知方法(Compressed Sensing或Compressive Sampling, CS)充分运用了大部分信号在预知的一组基上可以稀疏表示这一先验信息,利用随机投影实现了在远低于奈奎斯 特频率的采样频率下对压缩数据的直接采集.该方法不仅为降低采样频率提供了一种新思路,也为其它科学领域 的研究提供了新的契机.该文综述性地阐述了压缩感知方法的基本原理,给出了其中的一些约束问题和估计方法, 并介绍压缩感知理论的相关问题———矩阵填充,最后讨论了其未来可能的应用前景. (According to the conventional Shannon s sampling theorem,in order to represent the analog signal,the sampling rate should not be less than twice the Nyquist sampling rate.Howev- er,this theorem only makes use of the bandwidth information.As a result,the collected data contain many redundant information.The recently proposed sampling method,compressed sens- ing or compressive sampling(CS),can collect compressed data at the sampling rate much lower than that needed in Shannon s sampling theorem by exploring the compressibility of the signal. This paper presents a review on the basic theory of CS.Some of the restrictions and recovery methods in CS are also discussed.Finally,some potential applications based on CS are presented. )

用遗传算法解决一个np极难问题，即车间调度中的job shop问题。(With genetic algorithm is very difficult to solve a np problem, that is, the workshop dispatch of the job shop problem.)