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Neuromorphic Engineering

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Springer Handbook of Computational Intelligence

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Abstract

Neuromorphic engineering is a relatively young field that attempts to build physical realizations of biologically realistic models of neural systems using electronic circuits implemented in very large scale integration technology. While originally focusing on models of the sensory periphery implemented using mainly analog circuits, the field has grown and expanded to include the modeling of neural processing systems that incorporate the computational role of the body, that model learning and cognitive processes, and that implement large distributed spiking neural networks using a variety of design techniques and technologies. This emerging field is characterized by its multidisciplinary nature and its focus on the physics of computation, driving innovations in theoretical neuroscience, device physics, electrical engineering, and computer science.

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Abbreviations

AER:

address event representation

STDP:

spike-timing dependent plasticity

VLSI:

very large scale integration

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Authors and Affiliations

  1. Inst. Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland

    Giacomo Indiveri

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  1. Giacomo Indiveri
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Correspondence to Giacomo Indiveri .

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  1. Systems Research Inst., Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Indiveri, G. (2015). Neuromorphic Engineering. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_38

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_38

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