level-set

讲述了各种matlab在滤波器设计时可应用的函数，可供学习MATLAB的人使用。(About a variety of matlab filter design can be applied in a function, for people learning to use MATLAB.)

基于matlab的2FSK调制与仿真 m文件源程序(2FSK modulation)

此程序为在MATLAB环境下编写的模糊控制模块，通过模糊判断改变ＰＩＤ控制的参数，实现模糊ＰＩＤ控制。(This program is written in the MATLAB environment, fuzzy control module to change the PID control parameters, the fuzzy PID control, fuzzy judgment.)

AP聚类算法，很好用的聚类算法，matlab实现(AP clustering algorithm, well used clustering algorithm, matlab achieve)

矢量化编程技巧,基本的一些调试技巧，适合于初学者，非常有用(failed to translate)

brsola 解非线性方程 经典算法 改进版的拟牛顿叠代，收敛很快了(brsola solving nonlinear equations of classical algorithm for improved version of the quasi-Newton iteration, the convergence soon)

本文是基于MATLAB的具有时延和丢包的网络控制系统的补偿控制分析研究(Predictive Control of Network Control System w ith Network Delay and Data PacketDropout)

完美的OFDM系统的MATLAB仿真程序，希望对研究OFDM的同志有所帮助(Perfect simulation program MATLAB OFDM system, in the hope of OFDM help comrades)

利用小波分析对污染信号消噪以恢复原始信号(Using wavelet analysis of contamination signal to recover the original signal de-noising)

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)