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Issues in Analog VLSI and MOS Techniques for Neural Computing

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Part of the book series: The Kluwer International Series in Engineering and Computer Science ((SECS,volume 80))

Abstract

Issues in analog VLSI, such as the use of simple parameterized cells that are highly reconfigurable and input/output compatability, are being molded by the activities in developing hardware implementations of microelectronic neural networks. Analog MOS circuit modules, such as integrators, summers, and multipliers can be configured in a neural network architecture to build feedback/feedforward neural networks and/or the equivalent of adaptive, state-space signal processors. The methods of adaptation can be compared by evaluating a criterion or energy function which drives the adaptation process.

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© 1989 Kluwer Academic Publishers

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Bibyk, S., Ismail, M. (1989). Issues in Analog VLSI and MOS Techniques for Neural Computing. In: Mead, C., Ismail, M. (eds) Analog VLSI Implementation of Neural Systems. The Kluwer International Series in Engineering and Computer Science, vol 80. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1639-8_5

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  • DOI: https://doi.org/10.1007/978-1-4613-1639-8_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8905-0

  • Online ISBN: 978-1-4613-1639-8

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