sheffield_gatbx

MATLAB从入门到精通全书示例的源代码(MATLAB from entry to the source code of proficiency sample book)

基于SimMechanics的刚体系统建模mech-conveyor案例分析(SimMechanics modeling)

Mtalba Code for MPEG 1 2 3 4

文件中有11个文件夹，每个文件夹中含有十个左右实际工程例子的MATLAB实现PID算法的源代码(The Files has 11 folders, each folder contains about ten examples of practical engineering problems that MATLAB source code to solve PID algorithm )

拉丁超立方抽样，调用方式如下：S=lhs(m,dist,mu,sigma,lowb,upb) m: a scalar,the number of sample points dist: A row with distribution type flags of basic random variables the value of the flag can be 1 (for uniform distribution, 2(for normal distribution), 3(for lognormal) and 4(for extreme type 1). mu: A row vector comprising the mean value of basic random variables. sigma: A row vector with its length equaligng to mu,including the standard deviation of basic random variables. lowb: a row vector with its elements are the lower bound of the sampling interval upb:a row vector with its elements are the upper bounds of the sampling interval dist,mu,sigma,lowb,upb must have the same length. Output argument S: sampling point matrix, of which each row is a sampling point.(code of Latin Hypercube Sampling)

Script for computing BER with Binary Convolutional Code

主要利用matlab用于实现滤波器的建模(Realize the modeling of the filter)

MFDFA的计算原理及代码，全英文版，还有作图，编程代码步骤清楚。(MFDFA calculation principle and code, all in English, as well as mapping, programming code step clear.)

matlab设计 线性代数经典算法教程法classical algorithm for designing linear algebra matlab tutorial method(classical linear algebra algorithm design matlab tutorial method classical algorithm for designing linear algebra matlab tutorial method)

In this paper, we present two novel class-based weighting methods for the Euclidean nearest neighbor algorithm and compare them with global weighting methods considering empirical results on a widely accepted time series classification benchmark dataset. Our methods provide higher accuracy than every global weighting in nearly half of the cases and they have better overall performance. We conclude that class-based weighting has great potential for improving time series classification accuracy and it might be extended to use with other distance functions than the Euclidean distance.