MATLAB-GUI-listbox

基于台湾大学林智仁教授开发的LSSVM工具箱编写的鸢尾属植物分类程序，基于四个特征中的后两个进行的分类，分类效果相当好！(classification for iris data using lssvm)

说明：  CONTENTS CHAPTER 2 (C2 Folder) INTRODUCTION TO MATLAB/SIMULINK Exercise 1: Variable Frequency Oscillator SIMULINK file s1.mdl MATLAB m-file m1.m Exercise 2: Parallel RLC Circuit SIMULINK file s2.mdl MATLAB m-file m2.m MATLAB m-file m2init.m(1st half of m2.m) MATLAB m-file m2plot.m(2nd half of m2.m) Exercise 3: AC Energization of a RL Circuit SIMULINK file s3.mdl MATLAB m-file m3.m Exercise 4: Series RLC Resonant Circuit SIMULINK file s4.mdl MATLAB m-file m4.m

经过验证的维特比编译码MATLLAB程序，每行代码都有详细的备注 (Proven Viterbi than the codec MATLLAB program, each line of code to have detailed notes)

Convert LCC Lambert Conformal Conic to Geodesic coordination system from clark 1880 ellipsoid

用于信号特征提取、信号消噪，到达过程是的泊松过程，计算加权加速度,Relief计算分类权重，分析了该信号的时域、频域、倒谱，循环谱等,合成孔径雷达（SAR)目标成像仿真。( For feature extraction, signal de-noising, Arrival process is a Poisson process, Weighted acceleration, Relief computing classification weight, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. Synthetic Aperture Radar (SAR) imaging simulation target.)

把辨识分成两步进行：第一步：利用相关分析法获得对象的非参数模型（脉冲响应或相关函数）；第二步：利用最小二乘法、辅助变量法或增广最小二乘法等，进一步求的对象的参数模型。如果模型噪声与输入无关，则Cor-ls相关最小二乘法（二步法）可以得到较好的辨识结果。Cor-ls相关最小二乘法（二步法）实质上是先对数据进行一次相关分析，滤除了有色噪声的影响，再利用最小二乘法必然就会改善辨识结果。能适应较宽广的噪声范围，计算量不大，初始值对辨识结果影响较小。但要求输入信号与噪声不相关(The identification is divided into two steps: the first step: using the correlation analysis method for object nonparametric model (impulse response or related function) The second step: using the least squares method, auxiliary variable method or augmented least squares method and so on, further for the parameters of the object model. If the model input noise and independent, the Cor- ls related least squares (two footwork) can get good recognition results. Cor- ls related least squares (two footwork) is essentially the data to a correlation analysis, filter in addition to the influence of colored noise, using least squares inevitable will improve the identification result. To adapt to a wide range of noise and calculation is not big, the initial value to identification results less effect. But for the input signal and noise are not related)

Facial reconnaissance program

结构分析的有限元法与matlab程序设计4-1(Structural analysis of the finite element method and matlab programming 4-1)

Transmission matrix code

利用MATLAB实现遗传算法对非线性问题的求解，进行迭代计算(Genetic algorithms using MATLAB for solving nonlinear problems, iterative calculation)