Advances in Intelligent Signal Processing and Data Mining [electronic resource] : Theory and Applications / edited by Petia Georgieva, Lyudmila Mihaylova, Lakhmi C Jain.
Contributor(s): Georgieva, Petia [editor.] | Mihaylova, Lyudmila [editor.] | Jain, Lakhmi C [editor.] | SpringerLink (Online service).
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BookSeries: Studies in Computational Intelligence: 410Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XIV, 354 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642286964.Subject(s): Engineering | Artificial intelligence | Engineering | Engineering, general | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 620 Online resources: Click here to access online From the content: Introduction to Intelligent Signal Processing and Data Mining -- Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning -- A Sequential Monte Carlo Method for Multi-Target Tracking with the Intensity Filter -- Sequential Monte Carlo Methods for Localisation inWireless Networks -- A Sequential Monte Carlo Approach for Brain Source Localization.
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. .
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