This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.Contents:Learning Performance and EnhancementGeneralization and Performance EnhancementBasis Function Networks for ClassificationSelf-Organizing MapsClassification and Feature SelectionEngineering ApplicationsReadership: Postgraduates and researchers in neural networks, pattern recognition and electrical and electronic engineering.