Approximation of Multi-pattern to Single-Pattern Functions by Combining FeedForward Neural Networks and Support Vector Machines

Pakka, Vijaynarasimha Hindupur (2004) Approximation of Multi-pattern to Single-Pattern Functions by Combining FeedForward Neural Networks and Support Vector Machines. [Book Chapter]

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Abstract

In many fields there are situations encountered, where a function has to be estimated to determine its output under new conditions. Some functions have one output corresponding to differing input patterns. Such types of functions are difficult to map using a function approximation technique such as that employed by the Multilayer Perceptron Network. Hence to reduce this functional mapping to Single Pattern-to-Single Pattern type of condition, and then effectively estimate the function, we employ classification techniques such as the Support Vector Machines. This paper describes in detail such a combined technique, which shows excellent results for practical applications.

Item Type:	Book Chapter
Publication:	Applied computing, proceedings
Series.:	Lecture Notes in Computer Science
Publisher:	Springer V.B.
Additional Information:	copyright of this article belongs to Springer V.B.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	04 Dec 2008 08:34
Last Modified:	19 Sep 2010 04:52
URI:	http://eprints.iisc.ac.in/id/eprint/16575

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