SNR

simply a code try and get good knowledge on matlab

一个完整的PSO程序，可以实现优化，并且由很好的可视化见面，且可用来调节PID参数(A complete PSO program, you can optimize, and met by a good visualization, and can be used to adjust the PID parameters)

k最近邻算法，给出训练样本和测试样本，通过样本间欧氏距离或是绝对距离来寻找测试样本的k个近邻，并根据k个实例里多数所属的类将该测试样本归为该类。(k-nearest neighbor algorithm, given the training and testing samples by the Euclidean distance between the samples or the absolute distance to find the k nearest neighbors of the test sample and the test samples according to class k instances where the majority belongs classified as class .)

in this code random noise is denoise by wavelet and find the parameter for best wavelets

matlab 一些经典算法，包括数值拟合，回归，插值、解方程等(matlab some classic algorithms, including numerical fitting, regression, interpolation, solving equations, etc.)

The MATLAB code which encrypt data based on AES technique.

非线性动力学研究的入门matlab编写程序 主要有混沌 分岔概念的理解 (Getting matlab programming nonlinear dynamics of chaotic bifurcation of the main conceptual understanding)

it is a matlab introductory book...........

提取信号七个基于瞬时信息的特征：零中心归一化瞬时幅度功率谱密度的最大值,零中心归一化瞬时幅度绝对值的标准偏差，零中心非弱信号段瞬时相位非线性分量绝对值标准偏差，零中心非弱信号段瞬时相位非线性分量标准偏差，零中心归一化的非弱信号段瞬时频率绝对值的标准偏差，一个信号段的归一化瞬时频率功率谱密度的最大值，根据信号 QPSK 和16QAM在 XI 轴投影的不同表现，提出特征参数。(extract information based on the instan eous features : In the center is one of the instantaneous rate of the power spectral density of the maximum, is a center to the absolute value of the instantaneous rate of the standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component absolute standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component standard deviation, In the center is one of the non-weak signal of the absolute value of the instantaneous frequency standard deviation, a signal to one of the instantaneous frequency of the power spectral density of the maximum, According to 16QAM and QPSK signals XI axis projection in the different performance parameters raised.)

Its an IEEE paper about Energy Loss Minimization of Electricity Networks with Large Wind Generation using FACTS.