Self-adaptive systems for machine intelligence / Haibo He
Material type:
TextPublication details: Hoboken, N.J. : Wiley-Interscience, 2011Description: xvi, 230 p. : ill. ; 24 cmISBN: - 9780470343968 (hardback)
- 0470343966 (hardback)
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Open Shelf
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UMPLIB GAMBANG | Q325.5 .H44 2011 (Browse shelf(Opens below)) | 1 | Available | 0000061926 |
Includes bibliographical references and index
Introduction -- Incremental learning -- Imbalanced learning -- Ensemble learning -- Adaptive dynamic programming for machine intelligence -- Associative learning -- Sequence learning -- Hardware design for machine intelligence
"This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications"-- Provided by publisher
"This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain"-- Provided by publisher