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Titlebook: Neuromorphic Systems Engineering; Neural Networks in S Tor Sverre Lande Book 1998 Springer Science+Business Media New York 1998 VLSI.analog

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书目名称Neuromorphic Systems Engineering
副标题Neural Networks in S
编辑Tor Sverre Lande
视频video
丛书名称The Springer International Series in Engineering and Computer Science
图书封面Titlebook: Neuromorphic Systems Engineering; Neural Networks in S Tor Sverre Lande Book 1998 Springer Science+Business Media New York 1998 VLSI.analog
描述.Neuromorphic Systems Engineering: Neural Networks inSilicon. emphasizes three important aspects of this exciting newresearch field. The term .neuromorphic. expresses relations tocomputational models found in biological neural systems, which areused as inspiration for building large electronic .systems insilicon.. By adequate .engineering., these silicon systems aremade useful to mankind. ..Neuromorphic Systems Engineering: Neural Networks in Silicon.provides the reader with a snapshot of neuromorphic engineering today.It is organized into five parts viewing state-of-the-art developmentswithin neuromorphic engineering from different perspectives. ..Neuromorphic Systems Engineering: Neural Networks in Silicon.provides the first collection of neuromorphic systems descriptionswith firm foundations in silicon. Topics presented include:. large scale analog systems in silicon ..neuromorphic silicon .. auditory (ear) and vision (eye) systems insilicon .. learning and adaptation in silicon .. mergingbiology and technology .. micropower analog circuit design ..analog memory .. analog interchipcommunication on digital buses£/LIST£ ..Neuromorphic Systems Engineering: Neural Networks in Silico
出版日期Book 1998
关键词VLSI; analog; analog circuit design; communication; filter; model; network; networks; neural networks; speech
版次1
doihttps://doi.org/10.1007/b102308
isbn_softcover978-1-4757-8298-1
isbn_ebook978-0-585-28001-1Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 1998
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Analog VLSI Excitatory Feedback Circuits for Attentional Shifts and Trackingal processing in order to handle the overwhelming amount of sensory information that is available. Visual systems, such as those found in primates, have a hybrid architecture in which low-level processing is performed in parallel across the entire visual field, and high-level processing is only perf
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Introduction to Neuromorphic Communicationrmation coding found in our nerve-fibers seems to be quite inadequate for microelectronics. With a limited dynamic range of two to three orders of magnitude and poor noise margins, this kind of information coding may look like a bad choice from an engineering perspective.
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