Automatic-sorting-algorithm

说明：  Matlab数据统计和分析的程序，包含下面所列的多种算法的 MultiLineReg 用线性回归法估计一个因变量与多个自变量之间的线性关系 PolyReg 用多项式回归法估计一个因变量与一个自变量之间的多项式关系 CompPoly2Reg 用二次完全式回归法估计一个因变量与两个自变量之间的关系 CollectAnaly 用最短距离算法的系统聚类对样本进行聚类 DistgshAnalysis 用Fisher两类判别法对样本进行分类 MainAnalysis 对样本进行主成分分析(Matlab data and analysis procedures, listed below contain a variety of algorithms MultiLineReg estimated by linear regression of a dependent variable with a number of independent variables of the linear relationship between PolyReg estimation using a polynomial regression with dependent variable a variable relationship between CompPoly2Reg using quadratic polynomial regression method is estimated that fully a dependent variable and the two since the relationship between variables with the shortest distance CollectAnaly hierarchical clustering algorithm for clustering of samples with Fisher two types of DistgshAnalysis discriminant method to classify samples on the samples MainAnalysis principal component analysis)

基于粒子滤波，实现海面船只控制，滤除波动干扰，含建模和仿真，包括主程序和子程序(sea boat tracking and control based on PF)

ofdm系统中功率自适应分配算法研究的matlab源代码（k＝20）(ofdm Power System Adaptive Algorithm for the distribution of the source code Matlab (k = 20))

改进的NHT程序，可以对数据进行归一化，效果较以前的好(improved NHT method)

Matlab环境下实现的RBF神经网络K均值聚类算法(Matlab environment to achieve the RBF neural network K-means clustering algorithm)

matlab bootstrap程序设计方法(matlab bootstrap ?绦蛏????)

基于matlab软件的联络线功率波动风险评估的源代码(Matlab software-based tie-line power fluctuation risk assessment of the source code)

采用M2M4信噪比估计算法对QPSK调制解调器的接收端信噪比进行了估计(M2M4 SNR estimation algorithm on the the QPSK modem receiving end signal-to-noise ratio estimated)

one dimensional wave propagation along z axis passing from a material slab(dispersiv, conductive,etc.)

A motion picture presents a continues phenomena as a sequence of frames. We perceive continuity by "filling in the gaps" and "smoothing out " the missing information. While faster motion requires more frames during a given time period, there is a point where more frames per second yield no further improvement. The "sampling speed" must be fast enough to allow "appropriate averaging of dead times between frames", but need not accommodate motion too fast to be seen by a human. The above description is somewhat analogous to sampling of audio signals. The sampling rate depends on how fast the signals vary (the highest frequency we hear). Nyquist showed that sampling frequency exceeding twice the audio bandwidth is sufficient to include all the signal information, preserving the finest details up to half the sampling rate