Advances in Intelligent Signal Processing and Data Mining Theory and Applications

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 Carl...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Georgieva, Petia (-), Mihaylova, Lyudmila, Jain, Lakhmi C.
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg 2013.
Colección:Studies in Computational Intelligence ; 410.
Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b33045227*spi
Descripción
Sumario: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.  .
Descripción Física:XIV, 354 p.
Formato:Forma de acceso: World Wide Web.
ISBN:9783642286964