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Pré-Publication, Document De Travail Année : 2018

Energy efficient communication with neuro-inspired detector

Résumé

This paper focuses on the theoretical performance of a neuro-inspired digital communication, where the input signal is below the activation threshold of the neuron, making the noise crucial for the detection. We first derive the error probability of a neuro-inspired detector build upon a single Integrate-and-Fire (IF) neuron and then extend this result to a IF-based detector build upon multiple neurons. In this case, we propose to optimize the number of neurons in parallel, leading to an error probability of below 10 −4 for a large noise range, proving the strength of such a IF-based detector.
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Dates et versions

hal-01900990 , version 1 (22-10-2018)

Identifiants

  • HAL Id : hal-01900990 , version 1

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Anne Savard, Laurent Clavier, Francois Danneville, Christophe Loyez. Energy efficient communication with neuro-inspired detector. 2018. ⟨hal-01900990⟩
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