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Proceedings Paper

Noise-exploitation and adaptation in neuromorphic sensors
Author(s): Thamira Hindo; Shantanu Chakrabartty
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Paper Abstract

Even though current micro-nano fabrication technology has reached integration levels where ultra-sensitive sensors can be fabricated, the sensing performance (resolution per joule) of synthetic systems are still orders of magnitude inferior to those observed in neurobiology. For example, the filiform hairs in crickets operate at fundamental limits of noise; auditory sensors in a parasitoid fly can overcome fundamental limitations to precisely localize ultra-faint acoustic signatures. Even though many of these biological marvels have served as inspiration for different types of neuromorphic sensors, the main focus these designs have been to faithfully replicate the biological functionalities, without considering the constructive role of "noise". In man-made sensors device and sensor noise are typically considered as a nuisance, where as in neurobiology "noise" has been shown to be a computational aid that enables biology to sense and operate at fundamental limits of energy efficiency and performance. In this paper, we describe some of the important noise-exploitation and adaptation principles observed in neurobiology and how they can be systematically used for designing neuromorphic sensors. Our focus will be on two types of noise-exploitation principles, namely, (a) stochastic resonance; and (b) noise-shaping, which are unified within our previously reported framework called Σ▵ learning. As a case-study, we describe the application of Σ▵ learning for the design of a miniature acoustic source localizer whose performance matches that of its biological counterpart(Ormia Ochracea).

Paper Details

Date Published: 3 April 2012
PDF: 13 pages
Proc. SPIE 8339, Bioinspiration, Biomimetics, and Bioreplication 2012, 833905 (3 April 2012); doi: 10.1117/12.920189
Show Author Affiliations
Thamira Hindo, Michigan State Univ. (United States)
Shantanu Chakrabartty, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 8339:
Bioinspiration, Biomimetics, and Bioreplication 2012
Akhlesh Lakhtakia, Editor(s)

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