sanweipinpu3

说明：  探索分形奥秘,自然界与分形的关系，分形的由来(Explore the mysteries of fractal, the fractal nature and the relationship between the origin of fractal)

rate equation with simulink of matlab

一种用贝斯定理的形式基于压缩传感测量估计基本信号(employ a Bayesian formalism for estimating the undering signal based on compressive-sensing measurements )

matlab仿真。各种matlab的函数指令。很全，很有帮助。(matlab simulation. Matlab command of various functions. Very full and helpful.)

principal component analysis(PCA)主成分分析，Matlab实例代码(principal component analysis(PCA))

基于k近邻规则的PCA方法，改进的主元分析法用于故障诊断(PCA based on KNN)

MUSIC算法[1] 是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。MUSIC算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱，所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率，同时适应于任意形状的天线阵列，但是原型MUSIC算法要求来波信号是不相干的。(algorithm MUSIC is a method based on matrix feature space decomposition. From a geometric point of view, the signal processing of the observation space can be decomposed into signal subspace and noise subspace, it is clear that these two spaces are orthogonal. Signal subspace by the array received data covariance matrix and signal corresponding to the feature vector and noise subspace is by the covariance matrix of all minimum feature values (noise variance) corresponding to the feature vectors are composed. MUSIC algorithm is to use the orthogonal characteristics of these two complementary space to estimate the azimuth of spatial signals. All vectors of the noise subspace are used to construct spectral, and the peak position in all spatial azimuth spectra correspond to the direction of arrival of the signal. MUSIC algorithm greatly improves the direction finding resolution, and at the same time it is suitable for the antenna array of any shape, but the prototype MUSIC algorithm requir)

蚁群算法的一个程序，可以优化用来做机器人路径规划用(Ant colony algorithm is a procedure can be optimized to make use of robot path planning)

MATLAB simulation of group velocity dispersion in an optical fiber

说明：  W-矩阵置乱，效果比Arnold置乱更好(W-matrix scrambling, it is better than Arnold)