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DateConvert：简单而快速的日期转换 DateConvert转换DATESTR（0）格式的日期向量或序列号和日期向后。 Matlab的DATENUM，DATEVEC和DATESTR接受各种不同意见，但结果他们是缓慢的。如果输入格式正是众所周知，转换可以更快： DATENUM（ 17 - 10 - 2009 11时08分23秒 ）：2.97秒 DateConvert（ 17 - 10 - 2009 11时08分23秒 ， 号码 ）：0.039秒 =>“1.3％（1000环，1.5GHz的奔腾- M的，利用Matlab 7.7） DateConvert不*不*验证作为Matlab的日期函数输入日期： DATEVEC（ 32 - 2 - 2008 25:62:63 ）的答复[2008 3 4 2 2 7] DateConvert（ 32 - 2 - 2008 25:61:67 ， 载体 ）的答复[2008 2 32 25 61 67]！ 因此DateConvert几乎微不足道，但对速度进行了优化。我需要时间排序200 000邮票，并从217个减少到11秒的时间。 请运行单元测试TestDateVec检查的有效性和速度。 测试：利用Matlab 6.5，7.7，7.8，winxp的，32位。 纯Matlab代码，所以兼容性的MacOS，Linux操作系统，64位预期。 英语月份名称是必要的。(DateConvert: Simple but fast date conversion DateConvert converts the DATESTR(0) format to a date vector or serial date number and backwards. Matlab s DATENUM, DATEVEC and DATESTR accept a variety of inputs, but in consequence they are slow. If the input format is exactly known, the conversion can be much faster: DATENUM( 17-Oct-2009 11:08:23 ): 2.97 sec DateConvert( 17-Oct-2009 11:08:23 , number ): 0.039 sec => 1.3 (1000 loops, 1.5GHz Pentium-M, Matlab 7.7) DateConvert does*not* validate the input date as Matlab s date functions: DATEVEC( 32-Feb-2008 25:62:63 ) replies [2008 3 4 2 2 7], DateConvert( 32-Feb-2008 25:61:67 , vector ) replies [2008 2 32 25 61 67] ! So DateConvert is nearly trivial, but optimized for speed. I needed it for sorting 200 000 time stamps and reduced the time from 217 to 11 sec. Please run the unit-test TestDateVec to check validity and speed. Tested: Matlab 6.5, 7.7, 7.8, WinXP, 32bit. Pure Matlab code, so compat)

calculate the Gamma Correction for a particular image

matlab实用程序百例，关于图像处理的源码(matlab )

通信原理的MATLAB编程，满足对课本基础知识的理解，包括调制解调。(Communication Theory of the MATLAB programming to meet the basic knowledge to understand the textbook, including the modem.)

a gain calculator about semiconductor optical amplifier gain and ode method

rand 主要用于matlab中编程。主要是介绍rand的一些基本用法 大家有不懂得可以上网查(rand is for newer)

粒子滤波 PF( Particle Filtering) 是在 贝叶斯滤波框架下基于 Monte Carlo 采样的统计滤波方法，可解 决非线性、非高斯的滤波问题，声源跟踪就属于这类问题。近年 来，基于粒子滤波的声源跟踪算法已成为研究的热点。 (he real acoustic data recorded in a typi- cal meeting room using a small-scale microphone array is used for tracking experiments． Results show that the proposed algorithm can realise effectively the orientation tracking of the randomly walking speaker，in which，the root mean square error of tracking in direction of the hori- zontal angle and the elevation are all less than 5°． )

matlab simulink实现DCC滤波器，通信课程设计肯定用的到。(DCC filter matlab simulink realization, communication course design certainly used to.)

for edge filter. yoy can combain the matlab soft to BCB

The Viterbi decoder for convolutional codes