xPC_Target

说明：  认知无线电，退避策略，可用于学习，可运行，本人毕设研究内容(Cognitive radio, evasion strategy, can be used for learning, can be operated, I set up the research content.)

MathLab introduction in Romanian.

雷达目标检测仿真 正弦信号做自适应对消(Radar target detection sinusoidal signal simulation do adaptive cancellation)

稀疏分数阶傅里叶变换例子，线性调频信号的例子，分数阶傅里叶变换检测(Sparse fractional Fourier transform examples, linear frequency modulation signal example, fractional Fourier transform detection)

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)

this matlab code for Image contrast enhancements of grey and rgb images.

The PID controller is the most widely used controller in industrial systems. However, appropriately tuning a PID controller is not an easy task although it has only three parameters at most. This submission provides a tool for beginners to learn PID tuning.

QAM系统仿真，包括调制解调以及误码性能分析(QAM system simulation, including the modulation and demodulation and BER)

Game theory toolbox for matlab

随机一致性指标问题-Matlab实验课程学习资料，附源码(Random consistency index problem-Matlab experimental course learning materials, with a source)