Hidden Markov Models: Estimation and Control
by R. J. Elliott, L. Aggoun, J. B. Moore
Publisher: Springer 1995
Number of pages: 373
The aim of this book is to present graduate students with a thorough survey of reference probability models and their applications to optimal estimation and control. These new and powerful methods are particularly useful in signal processing applications where signal models are only partially known and are in noisy environments.
Download or read it online for free here:
by Sophocles J. Orfanidis
In this edition the emphasis is on real-time adaptive signal processing, eigenvector methods of spectrum estimation, and parallel processor implementations of optimum filtering and prediction algorithms, and including several new developments.
by Carl W. Helstrom - Prentice Hall
This is an introduction to signal-detection theory, a subject fundamental to the design of detectors of weak signals in the presence of random noise, and to the design of optimal receivers of communication, radar, sonar and optical signals.
by J. H. Karl - Academic Press
The book comprises a one-semester or self-study course, filling the gap between several oversimplified introductions and more topically specialized or formal treatments. Karl's book wins notable points for its easy reading style.
by Michele Basseville, Igor V. Nikiforov - Prentice-Hall
This book presents mathematical tools and techniques for solving change detection problems in wide domains like signal processing, controlled systems and monitoring. The book is intended for engineers and researchers involved in signal processing.