Neural Network Dynamics without Minimizing Energy
Joint Authors
Tsai, Feng-Sheng
Shih, Mau-Hsiang
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-4, 4 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-07
Country of Publication
Egypt
No. of Pages
4
Main Subjects
Abstract EN
Content-addressable memory (CAM) has been described by collective dynamics of neural networks and computing with attractors (equilibrium states).
Studies of such neural network systems are typically based on the aspect of energy minimization.
However, when the complexity and the dimension of neural network systems go up, the use of energy functions might have its own limitations to study CAM.
Recently, we have proposed the decirculation process in neural network dynamics, suggesting a step toward the reshaping of network structure and the control of neural dynamics without minimizing energy.
Armed with the decirculation process, a sort of decirculating maps and its structural properties are built here, dedicated to showing that circulation breaking taking place in the connections among many assemblies of neurons can collaborate harmoniously toward the completion of network structure that generates CAM.
American Psychological Association (APA)
Shih, Mau-Hsiang& Tsai, Feng-Sheng. 2013. Neural Network Dynamics without Minimizing Energy. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-4.
https://search.emarefa.net/detail/BIM-476291
Modern Language Association (MLA)
Shih, Mau-Hsiang& Tsai, Feng-Sheng. Neural Network Dynamics without Minimizing Energy. Abstract and Applied Analysis No. 2013 (2013), pp.1-4.
https://search.emarefa.net/detail/BIM-476291
American Medical Association (AMA)
Shih, Mau-Hsiang& Tsai, Feng-Sheng. Neural Network Dynamics without Minimizing Energy. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-4.
https://search.emarefa.net/detail/BIM-476291
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-476291