In this paper we present the growing hierarchical self-organizing map. This dynamically growing neural network model evolves into a hierarchical structure according to the requirem...
This paper extends a previous model where we examined the markets’ microstructure dynamics by using Genetic Programming as a trading rule inference engine, and Self Organizing Ma...
Michael Kampouridis, Shu-Heng Chen, Edward P. K. T...
In the previous papers (Pupeikis, 2000; Genov et al., 2006; Atanasov and Pupeikis, 2009), a direct approach for estimating the parameters of a discrete-time linear time-invariant (...
Abstract. Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Competitive learning in the SOM training process focusses on finding a neu...
With the rapid and dramatic increase in web feeds published by different publishers, providers or websites via Really Simple Syndication (RSS) and Atom, users cannot be expected t...