matlab-Trans

This is one of the best otmization numeric method.

小生境遗传算法程序 ％ MyFun1.m - 一维优化函数 ％ MyFun2.m - 二维优化函数 ％ MyFun3.m - 三维优化函数 ％ Main_GA1.m - 一维函数优化 - 主程序 ％ Main_GA2.m - 二维函数优化 - 主程序 ％ Main_GA3.m - 三维函数优化 - 主程序(Niching genetic algorithm procedure MyFun1.m- one-dimensional optimization function MyFun2.m- two-dimensional optimization function MyFun3.m- three-dimensional optimization function Main_GA1.m- one-dimensional function optimization- the main program Main_GA2.m- two-dimensional function optimization- the main program Main_GA3.m- three-dimensional function optimization- the main program)

Electromagnetic Simulation Using_Fdtd Sullivan2D书中的程序。(Electromagnetic Simulation Using_Fdtd Sullivan2D book program.)

MATLAB的灰色处理程序，好半天才弄好的，应该还行。(matlab)

说明：  matlab ocr for beginner

metodos numericos encontrar el minimo

包含优化类的几个简单示例程序，代码里有很完整的注释和解释，这是第二能量熵的matlab代码。( Optimization class contains several simple sample programs, Code, there are very complete notes and explanations This is the second energy entropy matlab code.)

包含光伏电池模块、MPPT模块、BOOST模块、逆变模块，包含位置式PID算法、积分分离式PID，包含了阵列信号处理的常见算法，MIMO OFDM matlab仿真。( PV modules contain, MPPT module, BOOST module, inverter module, It contains positional PID algorithm, integral separate PID, Contains a common array signal processing algorithm, MIMO OFDM matlab simulation.)

盲信号分离(BSS)是指在对彼此独立的源信号混合过程及各源信号本身均未知的情况下，从混合信号中分离出这些源信号的方法。BSS可以用来从多个麦克风混合语音信号中提炼出单个语音信号。本文简要阐述LMS、RLS算法，并通过仿真实验来分析比较这两类方法的性能，并利用此方法对一实际的语音信号进行分离。(Blind Signal Separation (BSS) is defined as independent of each other mixed-signal process and the source of the signal itself are unknown circumstances, from the mixed-signal to isolate the source of these signals. BSS can be used from multiple microphones mixed voice signal to extract a single speech signal. This paper briefly described LMS, RLS algorithm, and through simulation experiments to analyze the comparative performance of these two types of methods and take advantage of this method on a real speech signal separation.)

说明：   在高阶谱分析工具箱是一个M文件集合实施了多种先进的信号处理算法的频谱估计，polyspectral估计，时频分布计算，并包含许多实际应用如时延估计，谐波恢复，参数估计的Volterra（非线性）模型，以及自适应线性预测。其他潜在的应用包括音响，生物医学，经济学，地震勘探，无损检测，海洋学，等离子体物理，雷达，声纳，语音等(The Higher-Order Spectral Analysis Toolbox is a collection of M-files that implement a variety of advanced signal processing algorithms for spectral estimation, polyspectral estimation, and computation of time-frequency distributions, with applications such as time delay estimation, harmonic retrieval, parameter estimation of Volterra (nonlinear) models, and adaptive linear prediction. Other potential applications include acoustics, biomedicine, econometrics, exploration seismology, nondestructive testing, oceanography, plasma physics, radar, sonar, speech etc. )