Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences

Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 301)

Abstract

In this chapter, we compare the interval type-2 fuzzy logic system and perceptual computer, so as to eliminate confusion among researchers about whether or not there really are differences between them. We show that there are many more differences than similarities between them by focusing on the following six issues: inputs and membership functions, fuzzifier versus encoder, rules versus computing with words (CWW) engines, inference versus output of CWW engine, output processing versus decoder, and outputs versus recommendation plus data.

Keywords

Codebook Computing with words (CWW) CWW engine Defuzzification EKM algorithms Fuzzifier Fuzzy weighted average Interval type-2 fuzzy logic system Interval type-2 fuzzy sets Interval weighted average Jaccard similarity measure KM algorithms Linguistic weighted average Linguistic weighted power mean Novel weighted averages Perceptual computer Perceptual reasoning Rank Ranking band Rules Subjective judgments Similarity Subsethood Type-reduction Encoder 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Signal and Image Processing Institute, Ming Hsieh Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA

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