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Published in:
2010 | OriginalPaper | Chapter
Fuzzy Logic
Authors : Anupam Shukla, Ritu Tiwari, Rahul Kala
Published in: Towards Hybrid and Adaptive Computing
Publisher: Springer Berlin Heidelberg
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Logic forms a fundamental concept behind the manner in which a variety of works are performed. One tries to process the inputs based on reasoning or logic that helps in the generation of the outputs. In this chapter we first study fuzzy logic that is driven by fuzzy sets and fuzzy rules. Then we present the Fuzzy Inference Systems that use Fuzzy Logic for the generation of the outputs from the inputs. The logic base of these systems gives a clear understanding of the manner in which the system is operating. The chapter would present the various concepts of problem solving using Fuzzy Logic covering membership functions, fuzzy arithmetic and operators and finally the fuzzy inference systems. We also present the analogy of these systems with the Artificial Neural Networks and the design methodology in fuzzy systems. At the end the chapter focuses on the problems and limitations of the fuzzy systems that motivate their hybridization in form of hybrid computing systems that give a better performance.