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Pattern Recognition is a classic reference in the field which has been an invaluable resource preferred by students, academics, researchers, and other interested readers for more than four decades. Starting with the introductory concepts of pattern classification, the book lays the theoretical foundations of Bayesian decision theory and then focuses on key topics such as parameter estimation, discriminant analysis, neural networks, and nonmetric methods. It finally covers machine learning, unsupervised learning, and different clustering techniques. The book incorporates a host of pedagogical features, including worked examples, extensive graphics, expanded exercises, and computer project topics.||About the Author||Richard O. Duda is Professor in the Electrical Engineering Department at San Jose State University, San Jose, California. Peter E. Hart is Chief Executive Officer and President of Ricoh Innovations, Inc. in Menlo Park, California. David G. Stork is Chief Scientist, also at Ricoh Innovations, Inc.