Matlab

ImageDatastore is a useful function and can get a collection of image files, where each individual image fits in memory, but the entire collection of images does not necessarily fit.

rng function in Matlab can be used to generate a predictable sequence of numbers. This function provides the achieving the same results after the each training period in the context of the machine learning techniques. To achievemore information please click here.

In this example, we use sinusoidal wave and plot data several different figure.

The WFDB Toolbox for MATLAB and Octave is a collection of functions for reading, writing, and processing physiologic signals and time series in the formats used by PhysioBank databases (among others). The Toolbox is compatible with 64-bit MATLAB and GNU Octave on GNU/Linux, Mac OS X, and MS-Windows. To quick start to use offline WFDB Toolbox for Matlab http://physionet.org/physiotools/matlab/wfdb-app-matlab/wfdb-app-toolbox-0-9-6-1.zip  download this file.  Unzip file where you want. When unzip the file, mcode folder will create.  Open MATLAB.  Go where you unzip the file.  Write command line addpath(pwd) Finally write command line again savepath  You can use WFDB Toolbox offline anymore.  [tm,sig]=rdsamp('mitdb/100',1); plot(tm,sig);

Matlab Code % Source % http://www.dcs.gla.ac.uk/~srogers/firstcourseml/matlab/chapter7/pcaexample.html#2 clear all;close all; % Generate the data Y = [randn(20,2);randn(20,2)+5;randn(20,2)-5]; % Add 5 random dimensions N = size(Y,1); Y = [Y randn(N,5)];

In this work, We use PCA three dimensional data.  Matlab Code % PCA Model clear all, clc , close all hold on axis equal axis([-2 2 -2 2 -2 2]) % Step 1: Get some data X = [1 2 -1 -2 0; 0.2 0 0.1 0.2 -0.4; 1.2 0.3 -1 -0.1 -0.4]'; % Step 2: Substract the mean plot3(X(:,1),X(:,2),X(:,3),'ko'); XAdjust = X-repmat(mean(X),size(X,1),1); plot3(XAdjust(:,1),XAdjust(:,2),XAdjust(:,3),'ro'); % Step 3: Calculate the covariance matrix CM = cov(X); % Step 4: Eigenvalue and Eigenvector [V D]= eig(CM); % Step 5: Choosing component f1 = V(:,1)'; f2 = V(:,2)'; f3 = V(:,3)'; F=[f1; f2; f3];