9783030855581 - federated learning for iot applications (eai/springer innovations in communication and computing) (3 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2022
Serie: EAI/Springer Innovations in Communication and Computing, Buch 106 von 129. Buch 106 von 129 - EAI/Springer Innovations in Communication and Computing
- Hardcover
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Federated Learning for IoT Applications (EAI/Springer Innovations in Communication and Computing)
Yadav, Satya Prakash (Editor) / Bhati, Bhoopesh Singh (Editor) / Mahato, Dharmendra Prasad (Editor) / Kumar, Sachin (Editor)
Sprache: Englisch
Verlag: Springer 2022
Serie: EAI/Springer Innovations in Communication and Computing, Buch 106 von 129. Buch 106 von 129 - EAI/Springer Innovations in Communication and Computing
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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Hardcover. Zustand: Brand New. 273 pages. 9.25x6.10x0.69 inches. In Stock.
Sprache: Englisch
Verlag: Springer, Birkhäuser 2022
Serie: EAI/Springer Innovations in Communication and Computing, Buch 106 von 129. Buch 106 von 129 - EAI/Springer Innovations in Communication and Computing
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 128,39
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized mode…ls using data without intruding on users' privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federatedlearning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.
