Online learning and adaptive filters:

Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectra...

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Bibliographische Detailangaben
1. Verfasser: Diniz, Paulo Sergio Ramirez 1956- (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Cambridge, United Kingdom ; New York, NY, USA Cambridge University Press 2022
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Online-Zugang:BSB01
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Zusammenfassung:Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering
Beschreibung:Title from publisher's bibliographic system (viewed on 24 Nov 2022)
Beschreibung:1 Online-Ressource (xii, 253 Seiten)
ISBN:9781108896139
DOI:10.1017/9781108896139

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