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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Georgieva, Petia (Επιμελητής έκδοσης), Mihaylova, Lyudmila (Επιμελητής έκδοσης), Jain, Lakhmi C. (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Σειρά:Studies in Computational Intelligence, 410
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Advances in Intelligent Signal Processing and Data Mining  |h [electronic resource] :  |b Theory and Applications /  |c edited by Petia Georgieva, Lyudmila Mihaylova, Lakhmi C Jain. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XIV, 354 p.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 410 
505 0 |a 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. 
520 |a 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.  . 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Engineering, general. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Georgieva, Petia.  |e editor. 
700 1 |a Mihaylova, Lyudmila.  |e editor. 
700 1 |a Jain, Lakhmi C.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642286957 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 410 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-28696-4  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)