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

Foreword

It is my great pleasure to welcome the new book Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging by the prominent scientists Professor Sankar K. Pal and Professor Pradipta Maji.

Soft computing methods allow us to achieve high-quality solutions for many real-life applications. The characteristic features of these methods are tractability, robustness, low-cost solution, and close resemblance with human-like decision making. They make it possible to use imprecision, uncertainty, approximate reasoning, and partial truth in searching for solutions. The main research directions in soft computing are related to fuzzy sets, neurocomputing, genetic algorithms, probabilistic reasoning, and rough sets. By integration or combination of the different soft computing methods, one may improve the performance of these methods. Among the various integrations realized so far, neuro-fuzzy computing (combing fuzzy sets and neural networks) is the most visible one because of its several real-life applications.

Both fuzzy and rough set theory represent two different approaches to analyzing vagueness. Fuzzy set theory addresses gradualness of knowledge, expressed by the fuzzy membership, whereas rough set theory addresses the granularity of knowledge, expressed by the indiscernibility relation. In 1999, together with Professor Sankar K. Pal, we edited the book Rough-Fuzzy Hybridization published by Springer. Since then, great progress has been made in the development ...