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General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2012 Vol.1(3): 270-272 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2012.V1.72

Reduct Generation from Binary Discernibility Matrix: An Hardware Approach

Kanchan S. Tiwari, Ashwin G. Kothari, and Avinash G. Keskar

Abstract—Rough set theory is a powerful mathematical tool used for extracting useful rules from a huge database. We have proposed a Rough Set Machine which generates rules for classification applications. The classification task concentrates on predicting the value of the decision class for an object among a predefined set of classes’ values. This rough set machine uses the concept of discernibility matrix for calculating the reducts, and using these reducts it generates the rules which are used for classifying the objects. The Reduct block is synthesized and downloaded on FPGA.

Index Terms—Rough set, discernibility matrix, reduct, classification, FPGA .

K. S. Tiwari is with the MESCOE, Pune, Maharashtra, India.
A. G. Kothari and A. G. Keskar are with the VNIT, Nagpur, Maharashtra, India.

[PDF]

Cite: Kanchan S. Tiwari, Ashwin G. Kothari, and Avinash G. Keskar, "Reduct Generation from Binary Discernibility Matrix: An Hardware Approach," International Journal of Future Computer and Communication vol. 1, no. 3, pp. 270-272, 2012.

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