2. Rough-Fuzzy Hybridization and Granular Computing

  1. Pradipta Maji1 and
  2. Sankar K. Pal2

Published Online: 17 FEB 2012

DOI: 10.1002/9781118119723.ch2

Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging

Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging

How to Cite

Maji, P. and Pal, S. K. (2012) Rough-Fuzzy Hybridization and Granular Computing, in Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118119723.ch2

Author Information

  1. 1

    Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

  2. 2

    Center for Soft Computing Research, Indian Statistical Institute, Kolkata, India

Publication History

  1. Published Online: 17 FEB 2012
  2. Published Print: 27 JAN 2012

Book Series:

  1. Wiley Series on Bioinformatics: Computational Techniques and Engineering

Book Series Editors:

  1. Yi Pan and
  2. Albert Y. Zomaya

Series Editor Information

  1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

ISBN Information

Print ISBN: 9781118004401

Online ISBN: 9781118119723

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Keywords:

  • granular computing;
  • pattern recognition;
  • rough entropy;
  • rough-fuzzy computing

Summary

During the past decade, there have been several attempts to derive hybrid methods by judiciously combining the merits of fuzzy logic and rough sets under the name rough-fuzzy or fuzzy-rough computing. The result is a more intelligent and robust system providing a human interpretable, low cost, approximate solution, as compared to traditional techniques. This chapter discusses some of the theoretical developments relevant to pattern recognition. It first briefly introduces the necessary notions of fuzzy sets and rough sets. The chapter then discusses the concepts of granular computing and fuzzy granulation and emergence of rough-fuzzy computing. It presents a mathematical framework of generalized rough sets for uncertainty handling and defining rough entropy. Finally, the chapter discusses various roughness and entropy measures with properties.

Controlled Vocabulary Terms

fuzzy logic; fuzzy set theory; rough set theory