DocumentCode
1013184
Title
Analog neural network for support vector machine learning
Author
Perfetti, Renzo ; Ricci, Elisa
Author_Institution
Dept. of Electron. & Inf. Eng., Perugia Univ.
Volume
17
Issue
4
fYear
2006
fDate
7/1/2006 12:00:00 AM
Firstpage
1085
Lastpage
1091
Abstract
An analog neural network for support vector machine learning is proposed, based on a partially dual formulation of the quadratic programming problem. It results in a simpler circuit implementation with respect to existing neural solutions for the same application. The effectiveness of the proposed network is shown through some computer simulations concerning benchmark problems
Keywords
learning (artificial intelligence); neural chips; quadratic programming; support vector machines; analog neural network; partially dual formulation; quadratic programming problem; support vector machine learning; Application software; Circuits; Computer simulation; Kernel; Machine learning; Neural networks; Quadratic programming; Recurrent neural networks; Support vector machine classification; Support vector machines; Analog circuits; quadratic optimization; recurrent neural networks; support vector machines; Computers, Analog; Learning; Neural Networks (Computer);
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2006.875967
Filename
1650263
Link To Document