DocumentCode :
671426
Title :
Biologically inspired distributed sensor networks: Collective signal amplification via ultra-low bandwidth spike-based communication
Author :
Lundquist, S.Y. ; Paiton, D.M. ; Nowers, B.M. ; Schultz, P.F. ; Brumby, S.P. ; Jorgensen, Anders M. ; Kenyon, G.T.
Author_Institution :
Comput. Sci. Dept., New Mexico Inst. of Min. & Technol. (NMT), Socorro, NM, USA
fYear :
2013
fDate :
4-9 Aug. 2013
Firstpage :
1
Lastpage :
9
Abstract :
Wireless networks of biologically inspired distributed sensors (BIDS) are hypothesized to enable improved overall detection accuracy using ultra-low power and low bandwidth spike-based communication between nodes. Unlike traditional sensor networks, in which nodes communicate via digital protocols that require precise decoding of binary signal packets, BIDS nodes communicate by broadcasting generic radio frequency pulses, or spikes. Individual BIDS nodes are modeled after leaky integrate-and-fire (LIF) neurons, in which both filtered sensory signals and inputs from other BIDS nodes are accumulated as capacitive charge that decays with a characteristic time constant. A BIDS node itself broadcasts a spike whenever its internal state exceeds a threshold value. Here we present detailed simulations of a BIDS network designed to detect a moving target-modeled as a pure acoustic tone with a translating origin-against a background of 1/f noise. In the absence of a target, the average internal state is well below threshold and noise-induced spikes recruit little additional activity. In contrast, the presence of a target pushes the average internal state closer to threshold, such that each spike is now able to recruit additional spikes, leading to a chain reaction. Our results show that while individual BIDS nodes may be noisy and unreliable, a network of BIDS nodes is capable of highly reliable detection even when the signal-to-noise ratio (SNR) on individual nodes is low. We demonstrate that collective computation between nodes supports improved detection accuracy in a manner that is extremely robust to the damage or loss of individual nodes.
Keywords :
1/f noise; amplification; bio-inspired materials; digital communication; distributed sensors; neural nets; object detection; 1/f noise; BIDS nodes; biologically inspired distributed sensors; capacitive charge; collective signal amplification; leaky integrate-and-fire neurons; moving target detection; noise-induced spikes; signal-to-noise ratio; time constant; ultralow bandwidth spike-based communication; Mathematical model; Neurons; Peer-to-peer computing; Robustness; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location :
Dallas, TX
ISSN :
2161-4393
Print_ISBN :
978-1-4673-6128-6
Type :
conf
DOI :
10.1109/IJCNN.2013.6706765
Filename :
6706765
Link To Document :
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