Machine Intelligence
Haibo He
Sold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
New - Hardcover
Condition: New
Ships from Germany to U.S.A.
Quantity: 2 available
Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
Condition: New
Quantity: 2 available
Add to basketNeuware - 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.
Seller Inventory # 9780470343968
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.
Haibo He, PhD, is Assistant Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island. His primary research interest is computational intelligence and self-adaptive systems, including optimization and prediction, biologically inspired machine intelligence, machine learning and data mining, hardware design (VLSI/FPGA) for machine intelligence, as well as various application fields such as smart grid, sensor networks, and cognitive radio networks.
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