Local context discrimination in signature neural networks

Authors:
Roberto Latorre;Francisco B. Rodríguez;Pablo Varona
Affiliations:
Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain;Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain;Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Year:
2011

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Abstract

Bio-inspiration in traditional artificial neural networks (ANN) relies on knowledge about the nervous system that was available more than 60 years ago. Recent findings from neuroscience research provide novel elements of inspiration for ANN paradigms. We have recently proposed a Signature Neural Network that uses: (i) neural signatures to identify each unit in the network, (ii) local discrimination of input information during the processing, and (iii) a multicoding mechanism for information propagation regarding the who and the what of the information. The local discrimination implies a distinct processing as a function of the neural signature recognition and a local transient memory. In this paper we further analyze the role of this local context memory to efficiently solve jigsaw puzzles.