passa ai contenuti
Advances in intelligent signal processing and data mining : theory and applications Anteprima di questo documento
ChiudiAnteprima di questo documento
Stiamo controllando…

Advances in intelligent signal processing and data mining : theory and applications

Autore: Petia Georgieva; Lyudmila Mihaylova; L C Jain
Editore: Berlin ; New York : Springer, ©2013.
Serie: Studies in computational intelligence, 410.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Banca dati:WorldCat
Sommario:
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  Per saperne di più…
Voto:

(non ancora votato) 0 con commenti - Diventa il primo.

Soggetti
Altri come questo

 

Trova una copia online

Collegamenti a questo documento

Trova una copia in biblioteca

&AllPage.SpinnerRetrieving; Stiamo ricercando le biblioteche che possiedono questo documento…

Dettagli

Genere/forma: Electronic books
Tipo materiale: Document, Risorsa internet
Tipo documento: Internet Resource, Computer File
Tutti gli autori / Collaboratori: Petia Georgieva; Lyudmila Mihaylova; L C Jain
ISBN: 9783642286964 3642286968 364228695X 9783642286957
Numero OCLC: 805127658
Descrizione: 1 online resource.
Contenuti: Introduction to Intelligent Signal Processing and Data Mining / Lyudmila Mihaylova, Petia Georgieva and Lakhmi C. Jain --
Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning / Avishy Y. Carmi, Lyudmila Mihaylova, Amadou Gning, Pini Gurfil and Simon J. Godsill --
A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter / Marek Schikora, Wolfgang Koch, Roy Streit and Daniel Cremers --
Sequential Monte Carlo Methods for Localization in Wireless Networks / Lyudmila Mihaylova, Donka Angelova and Anna Zvikhachevskaya --
A Sequential Monte Carlo Approach for Brain Source Localization / Petia Georgieva, Lyudmila Mihaylova, Filipe Silva, Mariofanna Milanova and Nuno Figueiredo, et al. --
Computational Intelligence in Automotive Applications / Yifei Wang, Naim Dahnoun and Alin Achim --
Detecting Anomalies in Sensor Signals Using Database Technology / Gereon Schüller, Andreas Behrend and Wolfgang Koch --
Hierarchical Clustering for Large Data Sets / Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton and Badrinath Roysam --
A Novel Framework for Object Recognition under Severe Occlusion / Stamatia Giannarou and Tania Stathaki --
Historical Consistent Neural Networks: New Perspectives on Market Modeling, Forecasting and Risk Analysis / Hans-Georg Zimmermann, Christoph Tietz and Ralph Grothmann --
Reinforcement Learning with Neural Networks: Tricks of the Trade / Christopher J. Gatti and Mark J. Embrechts --
Sliding Empirical Mode Decomposition-Brain Status Data Analysis and Modeling / A. Zeiler, R. Faltermeier, A. M. Tomé, I. R. Keck and C. Puntonet, et al.
Titolo della serie: Studies in computational intelligence, 410.
Responsabilità: Petia Georgieva, Lyudmila Mihaylova, and Lakhmi C. Jain (eds.).
Maggiori informazioni:

Abstract:

With contributions from leading experts in the field, this volume presents the most efficient statistical and deterministic methods for information processing and applications that allow the  Per saperne di più…

Commenti

Recensioni editoriali

Sinossi editore

From the reviews: "This book is well structured and provides good coverage of several state-of-the-art approaches to intelligent signal processing and data mining. ... chapters contain examples and Per saperne di più…

 
Commenti degli utenti
Recuperando commenti GoodReads…
Stiamo recuperando commenti DOGObooks

Etichette

Diventa il primo.
Conferma questa richiesta

Potresti aver già richiesto questo documento. Seleziona OK se si vuole procedere comunque con questa richiesta.

Dati collegati


<http://www.worldcat.org/oclc/805127658>
library:oclcnum"805127658"
library:placeOfPublication
library:placeOfPublication
library:placeOfPublication
owl:sameAs<info:oclcnum/805127658>
rdf:typeschema:Book
schema:about
<http://id.worldcat.org/fast/1118288>
rdf:typeschema:Intangible
schema:name"Data mining."
schema:name"Signal processing--Digital techniques--Data processing"
schema:about
schema:about
schema:about
schema:about
schema:about
schema:about
<http://id.loc.gov/authorities/subjects/sh2010113085>
rdf:typeschema:Intangible
schema:name"Signal processing--Digital techniques--Data processing."
schema:bookFormatschema:EBook
schema:contributor
schema:contributor
schema:contributor
schema:copyrightYear"2013"
schema:datePublished"2013"
schema:description"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."
schema:exampleOfWork<http://worldcat.org/entity/work/id/1149580320>
schema:genre"Electronic books."
schema:inLanguage"en"
schema:name"Advances in intelligent signal processing and data mining theory and applications"
schema:publisher
schema:url<http://dx.doi.org/10.1007/978-3-642-28696-4>
schema:url<http://site.ebrary.com/id/10656389>
schema:url
schema:workExample
schema:workExample

Content-negotiable representations

Chiudi finestra

Per favore entra in WorldCat 

Non hai un account? Puoi facilmente crearne uno gratuito.