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Using Tags to Improve Diversity of Sparse Associative Memories

Authors:
Stephen Larroque
Ehsan Sedgh Gooya
Vincent Gripon
Dominique Pastor

Keywords: neural coding; associative memory; neural network; information theory; graph theory; sparse coding; clique; computational neuroscience.

Abstract:
Associative memories, a classical model for brain long-term memory, face interferences between old and new memories. Usually, the only remedy is to enlarge the network so as to retain more memories without collisions: this is the network's size--diversity trade-off. We propose a novel way of representing data in these networks to provide another mean to extend diversity without resizing the network. We show from our analysis and simulations that this method is a viable alternative, which can perfectly fit cases where network's size is constrained, such as neuromorphic FPGA boards implementing associative memories.

Pages: 1 to 7

Copyright: Copyright (c) IARIA, 2015

Publication date: March 22, 2015

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-390-2

Location: Nice, France

Dates: from March 22, 2015 to March 27, 2015