Lyapunov Stability Analysis of Gradient Descent-Learning Algorithm in Network Training
Author
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-07-05
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The Lyapunov stability theorem is applied to guarantee the convergence and stability of the learning algorithm for several networks.
Gradient descent learning algorithm and its developed algorithms are one of the most useful learning algorithms in developing the networks.
To guarantee the stability and convergence of the learning process, the upper bound of the learning rates should be investigated.
Here, the Lyapunov stability theorem was developed and applied to several networks in order to guaranty the stability of the learning algorithm.
American Psychological Association (APA)
Banakar, Ahmad. 2011. Lyapunov Stability Analysis of Gradient Descent-Learning Algorithm in Network Training. ISRN Applied Mathematics،Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-449345
Modern Language Association (MLA)
Banakar, Ahmad. Lyapunov Stability Analysis of Gradient Descent-Learning Algorithm in Network Training. ISRN Applied Mathematics No. 2011 (2011), pp.1-12.
https://search.emarefa.net/detail/BIM-449345
American Medical Association (AMA)
Banakar, Ahmad. Lyapunov Stability Analysis of Gradient Descent-Learning Algorithm in Network Training. ISRN Applied Mathematics. 2011. Vol. 2011, no. 2011, pp.1-12.
https://search.emarefa.net/detail/BIM-449345
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-449345