オンライン学習と適応フィルタ Online Learning and Adaptive Filters

Diniz, Paulo S. R./ de Campos, Marcello L. R./ Martins, Wallace A.

Cambridge University Press（2022/12発売）

• 製本 Hardcover:ハードカバー版／ページ数 300 p.
• 言語 ENG
• 商品コード 9781108842129
• DDC分類 621.3822

Full Description

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.

Contents

1. Introduction; 2. Adaptive filtering for sparse models; 3. Kernel-based adaptive filtering; 4. Distributed adaptive filters; 5. Adaptive beamforming; 6. Adaptive filtering on graphs.