Pattern Theory: The Stochastic Analysis of Real-World Signals, Second Edition

Like its widely praised, best-selling predecessor, Pattern Theory: The Stochastic Analysis of Real-World Signals, Second Edition treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. New to theSecond Edition:  • A new chapter discussing Convolutional Neural Networks (CNN’s) including the hierarchical structure of, and learning, with CNN’s •Additional topics, including flexible templates in medical applications, Gaussian models for texture synthesis, exponential models and their use.