Advances in Intelligent Signal Processing and Data Mining Theory and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Georgieva, Petia. (Editor), Mihaylova, Lyudmila. (Editor), Jain, Lakhmi C. (Editor)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: Studies in Computational Intelligence, 410
• Subjects: Engineering.; Artificial intelligence.; Engineering, general.; Artificial Intelligence (incl. Robotics).
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-28696-4
• Physical Description: XIV, 354 p. 143 illus. online resource.
• ISBN: 9783642286964
• ISSN: 1860-949X

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. � The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms. �