DocumentCode :
1756726
Title :
Memory Models of Adaptive Behavior
Author :
Traversa, Fabio Lorenzo ; Pershin, Yuriy V. ; Di Ventra, Massimiliano
Author_Institution :
Dept. of Electron. Eng., Univ. Autonoma de Barcelona, Barcelona, Spain
Volume :
24
Issue :
9
fYear :
2013
fDate :
Sept. 2013
Firstpage :
1437
Lastpage :
1448
Abstract :
Adaptive response to varying environment is a common feature of biological organisms. Reproducing such features in electronic systems and circuits is of great importance for a variety of applications. We consider memory models inspired by an intriguing ability of slime molds to both memorize the period of temperature and humidity variations and anticipate the next variations to come, when appropriately trained. Effective circuit models of such behavior are designed using: 1) a set of LC contours with memristive damping and 2) a single memcapacitive system-based adaptive contour with memristive damping. We consider these two approaches in detail by comparing their results and predictions. Finally, possible biological experiments that would discriminate between the models are discussed. In this paper, we also introduce an effective description of certain memory circuit elements.
Keywords :
LC circuits; biocomputing; damping; humidity; memristors; LC contours; adaptive response behavior; biological experiments; biological organisms; circuit models; electronic systems; humidity variations; memcapacitive system-based adaptive contour; memory circuit elements; memory models; memristive damping; slime molds; temperature variations; Adaptive frequency; amoeba; dynamical systems; learning; memcapacitive system; memory; memristor; synchronization;
fLanguage :
English
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2162-237X
Type :
jour
DOI :
10.1109/TNNLS.2013.2261545
Filename :
6525332
Link To Document :
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