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