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SPEA1 Algorithm for matlab Just run and enjoy

Logistic 逻辑映射，大家注意看啊(Logistic 逻辑映射)

大学物理实验 基于matlab的光学实验仿真(College physics experiment based on the optical experiment simulation matlab)

说明：  它主要研究的是多因变量对多自变量的回归建模，特别当各变量内部高度线性相关时，用偏最小二乘回归法更有效。另外，偏最小二乘回归较好地解决了样本个数少于变量个数等问题。 偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身。它与主成分分析法都试图提取出反映数据变异的最大信息，但主成分分析法只考虑一个自变量矩阵，而偏最小二乘法还有一个“响应”矩阵，因此具有预测功能。(It is mainly a result of the study is a multi-variable regression modeling and more independent variables, especially when the internal height of each variable linear correlation, partial least squares regression method is more effective. In addition, partial least squares regression solves the number of samples is less than the number of variables and other issues. Partial least squares method is a set of principal component analysis, canonical correlation analysis and multiple linear regression analysis of the advantages of the three methods in one. It is the principal component analysis are trying to extract the maximum information reflects data variability, but the principal component analysis considers only one independent variable matrix, and partial least squares and a &quot response&quot matrix, predictive capabilities.)

apply a lowpass filter to a watermarked audio signal to test the robustness input : vector representing the watermarked audio file output : vector representing the watermarked audio file corrupted by a highpass filter

褶积模型，褶积运算，地震褶积模型，反射系数与子波褶积运算(Convolution model, convolution operation, the seismic convolution model, reflection coefficient and wavelet convolution operation)

包括图像分析的四部分代码：matlab扩散和高斯函数，线性扩散，线性复扩散，非线性扩散。(It contains four parts： [1]MATLAB function:diffusion.m gauss.m [2]Linear diffusion Applying linear diffusion to images creating linear scale-space. MATLAB code: demo_lin.m Image: haifa1.bmp [3]Linear complex diffusion Applying linear complex diffusion creating Gaussian and Laplacian scale-spaces. MATLAB code: demo_cmplin.m [4]Nonlinear diffusions: Perona-Malik ["Anisotropic diffusion"] Catte et al. regularization of P-M Complex ramp-preserving diffusion Nonlinear edge preserving diffusions.The classical Perona-Malik process: the value of the diffusion coefficient is reduced near edges estimated by the first derivative. Best applied to step edges. A regularized version by Catte et al- the gradient estimation for controlling the process is smoothed by a Gaussian. Proved to be mathematically well-posed. Ramp preserving complex diffusion- best for ramp-type edges. Results are smoother with almost no staircasing effects. MATLAB code: demo_nldif.m Image: ct_scan.bmp)

说明：  该文件是极值算法的研究，包括一个主程序，一个最适应值程序和一个EO源程序，已通过系统仿真测试(The file is extremal algorithm, including a main program, one of the most fitness programs and a source EO has been tested by simulation)

说明：  对输入的一有理Z变换表达式（输入分子和分母系数序列），分别画出： （1）零极点图 （2）z在单位圆上时z变换所对应的DTFT的幅度谱和相位谱 （3）逆z变换所得序列，在各种不同的收敛域下（包括了右边序列，左边序列和双边序列的情况） (the importation of a rational expression Z-transform (input coefficient of the numerator and the denominator sequence), respectively paint : (1) The pole-zero plan (2) z in the unit circle at z transform the X corresponding to the amplitude spectrum and phase spectrum (3) Inverse z transform sequences derived from the convergence of various jurisdictions (including the right sequence, the sequence of the left and bilateral series))

雷达杂波的matlab仿真程序。包含各种概率和分布(Matlab radar clutter simulation program. Includes a variety of probability and distribution)