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这是关于卷积与Z和S映射的MATLAB源代码，含有基本操作的源代码，希望对大家有所帮助。(This is on the convolution with the Z and S mapping MATLAB source code, containing the basic operation of the source code, I hope to help all of you.)

最优化方法及其Matlab程序设计。包括带约束的罚函数法，复合形法，坐标轮换法，乘子法，单纯形法，割平面法，粒子群法，遗传算法等各种优化算法(Optimization method and Matlab programming. Including the penalty function method with constraints, the complex method, coordinate rotation method, the multiplier method, the simplex method, cutting plane method, particle swarm, genetic algorithm and other optimization algorithms)

此程序是初学matlab时练习的一个很好的范例，主要是进行M文件的书写。(Matlab beginner when this program is a good example of practice, mainly the M-file writing.)

TS模糊，包括聚类数选取，输入选择，前件辨识，后件辨识等(TS Fuzzy Model)

root music 算法估计精度更加优秀(root music The estimation accuracy of the algorithm is better)

matlab graph toolbox. It includes many algorithms which are used to find out a cycle basis and the shortest path of a graph

1)把您的联系电话号码 通过DTMF 编码生成为一个 .wav 文件。 2)对所生成的DTMF文件进行解码(1) put your contact phone number via DTMF codes generated as a. Wav file. 2) files generated by the DTMF decoder)

上述程序是美国RICE大学的一个学生编写的用于压缩感知的恢复算法，可以实现很多模型的稀疏恢复，包括BP，l1,l2,l1-l2混合型等比较多的类型(The above procedure is a student of the University of the United States RICE prepared for compressed sensing recovery algorithm can achieve a lot of model sparse recovery, including BP, l1, l2, l1-l2 hybrid more types)

3、 瑞利信道中的调制解调、信道估计： (1) 请推导出单径瑞利信道中的BPSK相干解调的理论误码率性能，并画出比特信噪比与误码率的关系曲线。 (2) 在单径瑞利信道中，请设计一种时分的导引辅助的信道估计方法，用Simulink进行仿真，测量BPSK的误码率性能，画出比特信噪比与误码率的关系曲线，并与(1)的曲线进行对比。 (3, the Rayleigh channel modulation and demodulation, channel estimation: (1) Please derive the single-path Rayleigh channel coherent demodulation of BPSK BER performance theory, and draw the signal to noise ratio and bit error rate curves. (2) single-path Rayleigh channel, please design a division of the guide-assisted channel estimation method, using Simulink simulation, measurement of the BER performance of BPSK, draw-bit signal to noise ratio and bit error rate curve, and with (1) of the curves were compared. )

very important to understand tomography of medical MRI images