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通过matlab模拟半导体激光器的动力学特性，通过调节反馈强度可以得到从弛豫震荡到混沌态的输出信号。(Matlab simulation by the dynamics of semiconductor lasers, can be obtained by adjusting the intensity of the feedback from the chaotic state of relaxation shocks to the output signal.)

此例要求供应中心到最远需求点的距离尽可能小(This case requires the demand supply center to the farthest point distance as small as possible)

基于宽带Marr子波的广义S变换程序，与常规S变换相比，时频聚焦性更高。(Generalized S transform broadband Marr wavelet-based program, compared with the conventional S-transform time-frequency focus more.)

基于matlab的相场案例，希望对各位有所帮助，如有不对，还请批评指正(Matlab-based phase-field case, they hope to be helpful, if wrong, criticism and)

本程序是希尔伯特黄变换中的EMD分解得到IMF分量的源程序(This procedure is the Hilbert-Huang transform EMD decomposition IMF component of the source)

1．用Matlab产生正弦波,矩形波,以及白噪声信号，并显示各自时域波形图 2．进行FFT变换，显示各自频谱图，其中采样率，频率、数据长度自选 3．做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱 4．用IFFT傅立叶反变换恢复信号，并显示恢复的正弦信号时域波形图(1. Produce sine wave, square wave, and the white noise signal with Matlab, and their time-domain waveform display 2. FFT transform, display each spectrum, where the sampling rate, frequency, length optional data 3. RMS to make maps of the three signals, power spectrum, as well as the number of RMS map 4. Restored by inverse Fourier transform IFFT signal and displays the time domain waveforms sinusoidal signal recovery)

用Baum-Welch算法来迭代估计一个隐马尔科夫模型（HMM）的初始状态概率分布以及其状态转移概率矩阵。其中文件有mainfile_B_W.m为主函数，Baum_Welch.m为Baum-Welch算法迭代函数，Forward_variable.m与Backward_variable.m与Gamma_variable.m与Ksi_variable.m是需要计算的四种因子，B_pdf.m为混淆散射概率密度函数。(It s Baum-Welch algorithm for iteratively estimating the initial states probability distribution and state transition probability matrix. In the folder, "mainfile_B_W.m" is the main function, and "Baum_Welch.m" is the iteration Baum-Welch function. Also these four file "Forward_variable.m " "Backward_variable.m" "Gamma_variable.m" "Ksi_variable.m" are used for calculating crucial factors. "B_pdf.m" is the emission probability distrubution function.)

说明：  可以方便地进行1,2范数的优化计算。具体针对稀疏恢复问题，最小二乘问题，约束优化问题的求解等。(It is convenient to optimize the calculation of 1,2 norms. Specifically for sparse recovery problem, least squares problem, constrained optimization problem and so on.)

说明：  2019年第16届华为杯数学建模F题第一问的代码(Code of the first question of mathematical modeling F of the 16th Huawei cup in 2019)

说明：  采用meanshift算法实现图像聚类，函数用matlab实现(clustering using Mean-shift)