A Distributed Outstar Network for Spatial Pattern Learning
Data(s) |
14/11/2011
14/11/2011
01/03/1993
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Resumo |
The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field of arbitrarily many nodes, whose activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse, whereby a path weight decreases in joint proportion to the transmitted path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals. Three synaptic transmission functions, by a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all. When source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the unit of long-term memory in such a system is an adaptive threshold, rather than the multiplicative path weight widely used in neural models. British Petroleum (89-A-1204); Advanced Research Projects Agency (ONR N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100) |
Identificador | |
Idioma(s) |
en_US |
Publicador |
Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems |
Relação |
BU CAS/CNS Technical Reports;CAS/CNS-TR-1993-036 |
Direitos |
Copyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission. Boston University Trustees |
Palavras-Chave | #Spatial pattern learning #Distributed coding #Outstar #Adaptive threshold #Rectified bias #Atrophy due to disuse #Transmission function #Neural networks |
Tipo |
Technical Report |