Prerequisites
Overview
In this laboratory you will experiment with the class of artificial Neural Networks (NN) known as SelfOrganizing Maps (SOM). The laboratory exercises are based on a Mathematica notebook. Download and open the notebook with Mathematica and then follow the instructions given for each exercise.
The Mathematica notebook for the exercise can be downloaded here.
Exercise 1: SOM basics
A detailed description of the exercise can downloaded here.
Exercise 2: The functions and parameters of the algorithm
detailed description of the exercise can downloaded here.
Exercise 3: The geometry of the input and output spaces
detailed description of the exercise can downloaded here.
Exercise 4: The training set
detailed description of the exercise can downloaded here.
Gallery: SOM Animations
LiveGraphics3D animations of the unfolding of a 3D, 2D, and 1D lattice in a 3D input space, with random uniform distribution of points in the input space. To show more clearly the initial ordering phase, the weights are randomly initialized to cover the whole input space, instead of being initially gathered in a small subpart of it.
3D lattice: 5x5x5
2D lattice: 5x20
2D lattice: 10x10
1D lattice: 150x
1D lattice: 100x
1D lattice: 100x
