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Neuromorphic Engineering: Overview

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Encyclopedia of Computational Neuroscience
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Definition

Neuromorphic engineering is a recent interdisciplinary field involving biologists, physicists, mathematicians, computer scientists, and engineers to design hardware/physical models of neural systems. It aims at designing silicon-based neural systems for computational or biomedical purposes. The term “neuromorphic” relates to the computational architecture, shaped to model biological neural systems: neuromorphic engineering is by essence strongly linked to computational neuroscience.

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Neuromorphic engineering offers an interesting alternative to computer simulations of neural networks: while main components of computers are high-precision high-speed digital hardware with high-power dissipation, neural components are slow asynchronous computational elements which use a combination of analog and digital signal representations. Neuromorphic systems are hardware implementations that operate in physical time; they are inspired by the structure, function, and...

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References

  • Mead C (1989) Analog VLSI and neural systems. Addison-Wesley, Reading

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Correspondence to Sylvie Renaud .

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© 2015 Springer Science+Business Media New York

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Renaud, S. (2015). Neuromorphic Engineering: Overview. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6675-8_765

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