radio

2006年World Congress on Intelligent Control and Automation上的一篇水平集的文章，对于初始化介绍比较详细(2006 World Congress on Intelligent Control and Automation on a level set of the article, for a more detailed introduction to initialize)

matlab实现自适应滤波器的仿真，包含m文件(adaptive filter matlab simulation file contains m)

说明：  LMI编程实例，可行性问题，最优控制，次优化问题等求解(LMI programming examples, optimal control, etc)

Spite压缩源码，matlab编写，希望对您能有很大帮助(Spite compressed source, Matlab prepared, and I hope to you can be of great help)

DFT and its circular nature

RLS算法实现,现代数字信号处理中一种典型的信号处理算法。(Rls algorithm useing in singnal and information processing.Rls algorithm useing in singnal and information processing.Rls algorithm useing in singnal and information processing.)

matlab编写的用卡尔曼滤波实现目标跟踪(matlab prepared using Kalman filter tracking)

说明：  用M文件写的模糊控制器，不是采用的模糊工具箱(M file written by the fuzzy controller, not using the fuzzy toolbox)

雷达系统分析与设计一书的部分matlab代码。《雷达系统分析与设计》是2008年由电子工业出版社编辑出版的马哈夫扎(MahafzaBassemR.美国)的电子通讯类专著。本书描述了雷达截面积、极化、匹配滤波器和雷达模糊函数及雷达波传播的最新进展，并给出了关于PRN码、多径和折射、高距离分辨率、杂波与MIT处理的有关内容。(Radar systems analysis and design of a part of the matlab code. Radar systems analysis and design in 2008 by the Electronic Press editor industrial publishing Mahafuzha (MahafzaBassemR. USA) electronic communications monographs. This book describes the radar cross section, polarization, and radar matched filter function fuzzy latest progress and radar transmission, and gives information about the PRN code, multipath and refraction, high range resolution, clutter and MIT-treated related content.)

克里金法假定采样点之间的距离或方向可以反映可用于说明表面变化的空间相关性。克里金法工 具可将数学函数与指定数量的点或指定半径内的所有点进行拟合以确定每个位置的输出值。克里金法是一个多步过程；它包括数据的探索性统计分析、变异函数建模 和创建表面，还包括研究方差表面。当您了解数据中存在空间相关距离或方向偏差后，便会认为克里金法是最适合的方法。该方法通常用在土壤科学和地质中。(This function completes what I have started with the functions variogram and variogramfit. It is not intended to be a highly optimized code for performing kriging but may have educational value. Note that for using kriging, you should download the latest version of variogramfit. kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform an ordinary kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the alg)