Online learning and adaptive filters - Diniz, Paulo Sergio Ramirez, 1956- (Cambridge, United Kingdom ; New York, NY, USA : Cambridge University Press, 2023)
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.
Title from publisher's bibliographic system (viewed on 24 Nov 2022).
Keywords: Adaptive signal processing -- Mathematics; Machine learning -- Mathematics; Signal processing -- Digital techniques -- Mathematics; Digital filters (Mathematics)