Document Detail

A neural support vector machine.
MedLine Citation:
PMID:  20092978     Owner:  NLM     Status:  MEDLINE    
Support vector machines are state-of-the-art pattern recognition algorithms that are well founded in optimization and generalization theory but not obviously applicable to the brain. This paper presents Bio-SVM, a biologically feasible support vector machine. An unstable associative memory oscillates between support vectors and interacts with a feed-forward classification pathway. Kernel neurons blend support vectors and sensory input. Downstream temporal integration generates the classification. Instant learning of surprising events and off-line tuning of support vector weights trains the system. Emotion-based learning, forgetting trivia, sleep and brain oscillations are phenomena that agree with the Bio-SVM model. A mapping to the olfactory system is suggested.
Magnus Jändel
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-01-11
Journal Detail:
Title:  Neural networks : the official journal of the International Neural Network Society     Volume:  23     ISSN:  1879-2782     ISO Abbreviation:  Neural Netw     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-04-26     Completed Date:  2010-07-22     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8805018     Medline TA:  Neural Netw     Country:  United States    
Other Details:
Languages:  eng     Pagination:  607-13     Citation Subset:  IM    
Copyright Information:
Copyright 2010 Elsevier Ltd. All rights reserved.
Agora for Biosystems, Box 57 SE-193 22, Sigtuna, Sweden; Swedish Defence Research Agency, SE-164 90, Stockholm, Sweden.
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MeSH Terms
Learning / physiology
Memory / physiology
Neural Networks (Computer)*
Neurons / physiology
Nonlinear Dynamics
Olfactory Pathways / physiology
Olfactory Perception / physiology
Pattern Recognition, Automated
Smell / physiology
Time Factors

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