Supervised and Unsupervised Pattern Recognition

"This book is an excellent source of knowledge of state-of-the-art feature extractionSupervised and unsupervised learning and training schemes are notable findsExciting applications of signal and image analysis and recognitionThis book provides in-depth guidance and inspiring ideas to new applications of signal and image analysis and recognition." --Tonglei Li, Ph.D., Purdue University, School of Pharmacy "great efforts have been made in a number of communities to explore solutions to pattern recognition problemsthis book describes their efforts made over ten researchers in the Neuroelectric and Neurocomputing Laboratories at Rutgers University. Along with concise introductory materials in pattern recognition, this volume presents several applications of supervised and unsupervised schemes to the classification of various types of signals and imagesUnlike other books in neural networks, this book gives an emphasis on feature extraction as well, which provides a systematic way to deal with pattern recognition problems in terms of neural networks and computational intelligenceit is worth noting that each chapter contains an extensive bibliography that provides a reliable list of good references. We believe that readers will find this list very useful to understand the materials in the book and cautious beginners in the related fields might benefit from this list as wellhelpful to a broad audience of graduate students, researchers, practicing engineers and professionals in computer and information science, electrical engineering, and biomedical informaticsthis book reflects the long-term continuous endeavors of a research group for conducting innovatory researches, which could provide someuseful hints to those novices in related fieldspioneering volumewelcomed by all interested in the fields of pattern recognition and computational intelligencethe editor's serious attempt to address the aforementioned issue must be welcomed by all interested in the fields of pattern recognition and computational intelligence and, therefore, this book deserves all credit." --Ke Chen, National Laboratory of Machine Perception and The Center for Information Science, Peking University, Beijing, China Promo Copy