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Towards Novel Neuroscience-Inspired Computing

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Book cover Emergent Neural Computational Architectures Based on Neuroscience

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2036))

Abstract

Present approaches for computing do not have the perfor- mance, flexibility and reliability of neural information processing sys- tems. In order to overcome this, conventional computing systems could benefit from various characteristics of the brain such as modular organi- zation, robustness, timing and synchronisation, and learning and memory storage in the central nervous system. This overview incorporates some of the key research issues in the field of biologically inspired computing systems.

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Authors and Affiliations

  1. Hybrid Intelligent Systems Group, University of Sunderland, St Peter’s Way, Sunderland, SR6 0DD, UK

    Stefan Wermter & Mark Elshaw

  2. Department of Computer Science, University of York, York, YO10 5DD, UK

    Jim Austin

  3. Institute for Adaptive and Neural Computation, University of Edinburgh, 5 Forrest Hill, Edinburgh

    David Willshaw

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  2. Mark Elshaw
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  3. Jim Austin
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Editors and Affiliations

  1. Centre of Informatics, SCET, University of Sunderland, St PetersWay, Sunderland SR6 0DD, UK

    Stefan Wermter

  2. Department of Computer Science, University of York, York, Y010 5DD, UK

    Jim Austin

  3. Institute for Adaptive and Neural Computation, University of Edinburgh, 5 Forrest Hill, Edinburgh, UK

    David Willshaw

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Wermter, S., Elshaw, M., Austin, J., Willshaw, D. (2001). Towards Novel Neuroscience-Inspired Computing. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_1

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