matlab_slowfeature

基于小波分析的信号奇异检测和去噪。。。。。。。。。。。。。。。(Based on wavelet analysis and signal singularity detection denoising. . . . . . . . . . . . . . .)

It is used for understanding the phenomenon of pendulum and chaos. It s good for beginners.

load flow solution for ieee 14 bus system is attached

matlab demystified nice book pretty good

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)

自己编的FIR滤波小程序，使用MATLAB编程，特点就是短小精悍~ (FIR；MATLAB)

实现了曲线拟合，关于客车燃油经济性的曲线(vc++ achieve numerical simulation with the approximation method of calculating least-squares curve fitting )

this program can plot phase plane linear and nonlinear system

最新的基于S函数的变步长自适应滤波算法，比传统的算法收敛速度更快(The latest variable step adaptive filtering algorithm based on S function is faster than the traditional algorithm converges )

DISCRETE COSINE TRANSFORM, SINE TRANSFORM, HADAMARD KERNEL, HAAR KERNEL , MEDIAN FILTERING