This book presents a collection of seminal papers on fuzzy pattern recognition, edited by James C. Bezdek and Sankar K. Pal. It covers the theory and applications of fuzzy sets in pattern recognition, starting with Zadeh's 1965 paper on fuzzy sets and proceeding chronologically through the development of fuzzy algorithms for feature analysis, clustering, classifier design, neural network learning, image processing, and computer vision. Each chapter includes an introduction, comments on the importance of the selected papers, and a bibliography. The book is suitable for scientists and engineers in academia, industry, and government who work on systems that process sensor data for classification, prediction, and control. It can also serve as a supplementary text for courses in fuzzy sets, classifier design, cluster analysis, feature analysis, image processing, and computational models for uncertain reasoning. The material is appropriate for senior undergraduates and first-year graduate students in engineering and the physical and computational sciences. The volume was commissioned by the IEEE Neural Networks Council, which has supported fuzzy conferences, the IEEE Transactions on Fuzzy Systems, and books on fuzzy pattern recognition. The authors thank the NNC and its leaders for their support, as well as the readers who provided valuable feedback. They also acknowledge the staff at IEEE Press, particularly Dudley Kay and Karen Miller, for their outstanding work in producing the book under tight deadlines.This book presents a collection of seminal papers on fuzzy pattern recognition, edited by James C. Bezdek and Sankar K. Pal. It covers the theory and applications of fuzzy sets in pattern recognition, starting with Zadeh's 1965 paper on fuzzy sets and proceeding chronologically through the development of fuzzy algorithms for feature analysis, clustering, classifier design, neural network learning, image processing, and computer vision. Each chapter includes an introduction, comments on the importance of the selected papers, and a bibliography. The book is suitable for scientists and engineers in academia, industry, and government who work on systems that process sensor data for classification, prediction, and control. It can also serve as a supplementary text for courses in fuzzy sets, classifier design, cluster analysis, feature analysis, image processing, and computational models for uncertain reasoning. The material is appropriate for senior undergraduates and first-year graduate students in engineering and the physical and computational sciences. The volume was commissioned by the IEEE Neural Networks Council, which has supported fuzzy conferences, the IEEE Transactions on Fuzzy Systems, and books on fuzzy pattern recognition. The authors thank the NNC and its leaders for their support, as well as the readers who provided valuable feedback. They also acknowledge the staff at IEEE Press, particularly Dudley Kay and Karen Miller, for their outstanding work in producing the book under tight deadlines.