Perceptual Computing

This book focuses on the three components of a Perceptual Computer—encoder, CWW engines, and decoder—and then provides detailed applications for each. It uses interval type-2 fuzzy sets (IT2 FSs) and fuzzy logic as the mathematical vehicle for perceptual computing, because such fuzzy sets can model first-order linguistic uncertainties whereas the usual kind of fuzzy sets cannot. Drawing upon the work on subjective judgments that Jerry Mendel and his students completed over the past decade, Perceptual Computings hows readers how to: • Map word-data with its inherent uncertainties into an IT2 FS that captures these uncertainties • Use uncertainty measures to quantify linguistic uncertainties • Compare IT2 FSs by using similarity and rank • Compute the subsethood of one IT2 FS in another such set • Aggregate disparate data, ranging from numbers to uniformly weighted intervals to nonuniformly weighted intervals to words • Aggregate multiple-fired IF-THEN rules so that the integrity of word IT2 FS models is preserved hows readers how to: • Map word-data with its inherent uncertainties into an IT2 FS that captures these uncertainties • Use uncertainty measures to quantify linguistic uncertainties • Compare IT2 FSs by using similarity and rank • Compute the subsethood of one IT2 FS in another such set • Aggregate disparate data, ranging from numbers to uniformly weighted intervals to nonuniformly weighted intervals to words • Aggregate multiple-fired IF-THEN rules so that the integrity of word IT2 FS models is preserved