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Online Learning and Adaptive Filters

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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.

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Product Details
Cambridge University Press
1108902243 / 9781108902243
eBook (Adobe Pdf)
23/11/2022
United Kingdom
English
300 pages
Copy: 10%; print: 10%
Print on demand edition Description based on CIP data; resource not viewed.