Towards an effective multi-map self organizing recurrent neural network
Abstract
This paper presents a multi-map joint self-organizing architecture able to represent non-markovian temporal sequences. The proposed architecture is inspired by previous works based on dynamic neural fields. It provides a faster and easier to handle architecture making it easier to scale to higher dimensional machine learning problems.