PCA is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities and differences. Below are the steps of the algorithm: close all; % clear all; clc; % data = load('Data/eeg.mat'); % data = data.data{1,2}; Step 1 – Initialize the dataset, 6 vectors of 32 sample data % % Step 1 - Initialize the dataset, 6 vectors of 32 sample data % X =...
