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Learning in Neural Networks: VLSI Implementation StrategiesFully-parallel hardware neural network implementations may be applied to high-speed recognition, classification, and mapping tasks in areas such as vision, or can be used as low-cost self-contained units for tasks such as error detection in mechanical systems (e.g. autos). Learning is required not only to satisfy application requirements, but also to overcome hardware-imposed limitations such as reduced dynamic range of connections.
Document ID
20060041781
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Duong, Tuan Anh
Date Acquired
August 23, 2013
Publication Date
January 1, 1995
Publication Information
Publication: Fuzzy Logic and Neural Network Handbook
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Distribution Limits
Public
Copyright
Other
Keywords
Neural Networks