Principal Component Analysis (PCA) is an effective tool for dimensionality reduction, transforming high dimensional data into a representation that has fewer dimensions (although these dimensions are not from the original set of dimensions). 421 kata lagi

## Tag » Matlab

#### Histogram Equalization Using MATLAB

The first time I did a real image processing using matlab is when I took ECE172. For this homework, I was given a very low contrast x-ray image. 213 kata lagi

#### Scilab as a free Numerical Computing package for Institutions

The basic purpose for this write-up is share a Control System’s Lab Manual that I prepared, based upon the use of Scilab and its modelling and simulation package Xcos. 525 kata lagi

#### Intro to my Blog

This is my first blog, and blog post, so I just want to explain here what this blog is about. Simply put, there is lots of material that I want to share with the world; what material? 82 kata lagi

#### Merge Sort

Another implementation of an algorithm in Matlab from the Stanford Coursera series. This time, I got some help from some code per the link below: 217 kata lagi

#### Simple Matlab implementation of Karatsuba Algorithm

While doing the Standford Algorithm course hosted on the Coursera website, I will attempt to implement the algorithms in Matlab and post here.

81 kata lagi

function sol = Karatsuba(x,y)

#### RBFN Tutorial Part II - Function Approximation

A number of people have asked me, in response to my tutorial on Radial Basis Function Networks (RBFNs) for classification, about how you would apply an RBFN to function approximation or regression (and for Matlab code to do this, which you can find at the end of the post). 986 kata lagi