Reference : Online Learning and Adaptive Filters
Books : Book published as author, translator, etc.
Engineering, computing & technology : Electrical & electronics engineering
Security, Reliability and Trust
http://hdl.handle.net/10993/52999
Online Learning and Adaptive Filters
English
Diniz, Paulo S. R. [Federal University of Rio de Janeiro]
de Campos, Marcello L. R. [Federal University of Rio de Janeiro]
Alves Martins, Wallace mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Lima, Markus V. S. [Federal University of Rio de Janeiro]
Apolinário Jr., José A. [Instituto Militar de Engenharia]
2022
Cambridge University Press
250
978-1-108-84212-9
[en] 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.
http://hdl.handle.net/10993/52999
10.1017/9781108896139
https://doi.org/10.1017/9781108896139

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