An Optimal Implementation on FPGA of a Hopfield Neural Network
Joint Authors
Ziade, H.
Velazco, R.
EL Falou, W.
Mansour, W.
Ayoubi, R.
Source
Advances in Artificial Neural Systems
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-08-22
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
The associative Hopfield memory is a form of recurrent Artificial Neural Network (ANN) that can be used in applications such as pattern recognition, noise removal, information retrieval, and combinatorial optimization problems.
This paper presents the implementation of the Hopfield Neural Network (HNN) parallel architecture on a SRAM-based FPGA.
The main advantage of the proposed implementation is its high performance and cost effectiveness: it requires O(1) multiplications and O(log N) additions, whereas most others require O(N) multiplications and O(N) additions.
American Psychological Association (APA)
Mansour, W.& Ayoubi, R.& Ziade, H.& Velazco, R.& EL Falou, W.. 2011. An Optimal Implementation on FPGA of a Hopfield Neural Network. Advances in Artificial Neural Systems،Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-453068
Modern Language Association (MLA)
Mansour, W.…[et al.]. An Optimal Implementation on FPGA of a Hopfield Neural Network. Advances in Artificial Neural Systems No. 2011 (2011), pp.1-9.
https://search.emarefa.net/detail/BIM-453068
American Medical Association (AMA)
Mansour, W.& Ayoubi, R.& Ziade, H.& Velazco, R.& EL Falou, W.. An Optimal Implementation on FPGA of a Hopfield Neural Network. Advances in Artificial Neural Systems. 2011. Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-453068
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453068
