Modified growing neural gas algorithm for faster convergence on signal distribution sudden change
Date Issued
2009-10-29
Author(s)
Gancev, Stojancho
Abstract
The paper deals with the problem of faster optimal
coverage of a Growing Neural Gas algorithm for random
signals appearing with non-stationary distributions. A
modification of the algorithm that successfully solves this
problem will be presented with simulations in a 2-D
environment and statistical results that will show its efficiency.
A comparison with a previous solution for the same problem
using so called Utility measure will be also given.
