time-frequency

windows gui wrapper for fb

基于HHT的matlab实现，通过EMD对信号进行分解，利用HHT变化得到时频谱(Based on the signal matlab HHT transform implementor)

一种实现复矩阵的SVD分解的算法，使用Matlab进行仿真，亲测可用。(SVD decomposition algorithm to achieve complex matrix, using Matlab to simulate pro-test is available.)

FDTD+PML计算光子晶体的程序，很有价值的哦(FDTD+ PML procedure for calculating the photonic crystal, valuable Oh)

(2). 采用汉明窗，分段长度L=32，用修正的周期图法进行谱估计，并分析数据长度N，分段长度M对谱估计结果的影响。((2) using Hamming window, segment length L = 32, the modified periodogram method of spectral estimation and analysis of data length N, the length M of the sub-spectrum estimation results.)

Optimization toolbox

实现一阶滤波器系数的可调，虽数据段的突出变化，实时调节滤波器系数，实现对数据的平滑滤波(The first-order filter coefficients can be adjusted, although the prominent changes in the data segment, real-time adjustment of filter coefficients, the filtering of data)

说明：  《MATLAB与控制系统仿真实践》 源程序 数据(MATLAB and Control System Based Practice source data)

MIDACO是一般的优化问题求解器。 MIDACO可应用于连续（NLP），离散/整数（IP）和混合整数（MINLP）的问题。问题可能被限制在平等和/或不等式约束。 MIDACO适合多达数百至几千优化变量的问题。 MIDACO实现了一个自由衍生物，启发式算法的处理方法处理的问题，因为黑盒可含有关键功能特性，如非凸性，不连续或随机噪声。(MIDACO is a solver for general optimization problems. MIDACO can be applied to continuous (NLP), discrete/integer (IP) and mixed integer (MINLP) problems. Problems may be restricted to equality and/or inequality constraints. MIDACO is suitable for problems with up to several hundreds to some thousands of optimization variables. MIDACO implements a derivative-free, heuristic algorithm that treats the problem as black-box which may contain critical function properties such as non-convexity, discontinuities or stochastic noise.)

随机固定求和函数，里面附有具体的应用讲解，可参考。(Random fixed sum function, which accompanied the application of specific explanations, can be found.)