Matlab_tool_box

1) 已知x=[1:15], y=[12 34 56 78 99 123 165 198 243 277 353 345 303 288 275], 用多项式进行拟合，给出拟合多项式，(所选拟合多项式阶数不同，拟合结果不同，请你选择适当的阶数进行拟合)，并绘出原始数据点、拟合曲线和95％置信区间（confidence bounds）的图形 . 2) 根据下面数学模型建立仿真模型，并在一个示波器中把它们的波形仿真出来。 (1) are known to x = [1:15], y = [12 34 56 78 99 123 165 198 243 277 353 345 303 288 275], with polynomial fitting, given the polynomial fitting, (the election order polynomial fitting different fitting results to differ, please select the appropriate order of fit), and draw original data points, fitting curve and 95 confidence interval (confidence bounds) graphics .2 ) In accordance with the following mathematical model for the establishment of simulation model, and in an oscilloscope waveform in their simulation out.)

计算一定功率抽运光作用下单掺Tm光纤激光器稳态时沿光纤方向粒子数分布(Calculation of a certain pump power under a single Tm-doped fiber laser at steady state along the fiber direction of particle number distribution)

粒子群算法（PSO）的优化程序，通用，很好用的。。(PSO Optimization program)

说明：  卷积码的MATLAB仿真及其性能测试，包括卷积码的编码和VITERBI译码程序(Convolutional codes of MATLAB simulation and performance testing, including the convolutional code encoding and decoding procedures VITERBI)

这是用itpp库编写的卷积码的解码程序。由于用C++库和Intel的MKL库，所以速度飞快。同样的仿真点数， Matlab2012下用了15分半钟，而这个程序仿真只用了半分钟，相当于是matlab速度的30多倍。(This is itpp prepared for the convolutional code decoding process. Because with C++ libraries and Intel' s MKL library, so fast. The same simulation points under Matlab2012 spent 15 and a half minutes, and this program simulation with only half a minute, the equivalent of 30 times the speed of matlab.)

说明：  matlab粒子群优化（Particle Swarm Optimization, PSO）算法(Particle Swarm Optimization)

BivaShrink方法、模型1、模型2、模型3（TrivaShrink方法）、BayesShrink方法、 LAWMLShrink方法的DWT实现和DT_CWT实现。(BivaShrink method, model 1, model 2, model 3 (TrivaShrink method), BayesShrink methods, LAWMLShrink methods DT_CWT realization and the realization of DWT.)

说明：  基于小波变换与正交匹配准备恢复算法的稀疏恢复算法试验(Orthogonal wavelet transform algorithm is ready to resume Test match)

高斯脉冲在光纤中的演变，用MATLAB程序实现(gaussian pulse evolution)

使用DC算法求解非凸函数的最优化问题。可以确保局部最优解，有时收敛到全局最优(DC algorithm using optimization problem of non-convex function. Ensure local optima, sometimes converge to the global optimum)