NDLI: Chaotic control of deterministic variability in a BAM-inspired model of memory

Content Provider	IEEE Xplore Digital Library
Author	Nejadgholi, I. Seyyedsalehi, S.A.
Copyright Year	2010
Description	Author affiliation: Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran (Nejadgholi, I.; Seyyedsalehi, S.A.)
Abstract	According to some biological observations, generating output variability is one of the characteristics expected from a memory model. In this paper a BAM inspired chaotic model is used to mimic this functionality of the brain. Chaos gives the potential to create deterministic variability and control its degree of uncertainty. Using some time series generated by the trained network, largest lyapunov exponent is computed for different values of transient parameter of neurons' activation functions. Critical values of this parameter leading to most chaotic behavior for each neuron are stored and used to set the network during recall. Exhibiting desired behaviors with various degrees of uncertainty is achieved as a product of a complex interaction between a group of chaotic neurons and another group behaving in a fixed point manner.
Starting Page	203
Ending Page	208
File Size	419716
Page Count	6
File Format	PDF
ISBN	9781424481347
e-ISBN	9781424481361
DOI	10.1109/ISDA.2010.5687264
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Chaos chaos theory lyapunov exponent deterministic variability Computational modeling Neurons Feature extraction Trajectory Mathematical model memory model
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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