NDLI: Learning state space trajectories in cellular neural networks

Content Provider	IEEE Xplore Digital Library
Author	Schuler, A.J. Nachbar, P. Nossek, J.A. Chua, L.O.
Copyright Year	1992
Description	Author affiliation: Inst. for Network Theory & Circuit Design, Tech. Univ. of Munich, Germany (Schuler, A.J.; Nachbar, P.; Nossek, J.A.)
Abstract	A learning algorithm similar to the backpropagation-through-time approach is presented. The algorithm is based on the minimization of an error criterion, which is defined as the product of a function of the state at a given time and the integral of an entire time function of the state over the trajectory prior to this time. The technique of the calculus-of-variation is used to evaluate the gradient of the error in the parameter space, which can be used to descend to a minimum on the error surface. This theory is adapted to cellular network networks (CNNs) and some simple examples of the learning of CNN parameters are shown.<>
Starting Page	68
Ending Page	73
File Size	303649
Page Count	6
File Format	PDF
ISBN	0780308751
DOI	10.1109/CNNA.1992.274353
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-10-14
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State-space methods Intelligent networks Cellular neural networks Backpropagation algorithms Differential equations Neural networks Time measurement Circuit synthesis Laboratories Educational institutions
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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