Pattern recognition. An algorithmic approach.
This interesting book provides a concise and simple exposition of principal topics in pattern recognition using an algorithmic approach, and is intended mainly for undergraduate and postgraduate students. The book is divided into 11 chapters, illustrating the following subjects: representation, nearest neighbour based classifiers, Bayes classifier, hidden Markov models, decision trees, support vector machines, combination of classifiers, clustering. An application to handwritten digit recognition is described at the end of the book. Many examples and exercises are proposed to make the treatment clear. A ``further reading'' section and a bibliography are presented at the end of each chapter. The mathematical treatment is mostly at an elementary level.
scientific article; zbMATH DE number 5866341