Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system

Bioinspiration and Biomimetics

Volumn 11, Issue 2, 2016, Pages

  Diamond, A ^a   Schmuker, M ^a   Berna, A Z ^b   Trowell, S ^b   Nowotny, Thomas ^a  

^a UNIVERSITY OF SUSSEX   (United Kingdom)

^b CSIRO   (Australia)

Author keywords

bioinspired neural networks; classification; electronic noses; insect olfaction

Indexed keywords

BIOMIMETICS; CLASSIFICATION (OF INFORMATION); METALS; NEURAL NETWORKS; NEURONS;

BIO-INSPIRED NEURAL NETWORK; GENERIC CLASSIFIER; INSECT OLFACTION; METAL OXIDE SENSORS; NEURONAL NETWORKS; OLFACTORY SYSTEMS; SPIKING NETWORKS; SPIKING NEURAL NETWORKS;

ELECTRONIC NOSE;

OLFACTORY RECEPTOR;

ANIMAL; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; BIOMIMETICS; COMPUTER SIMULATION; COMPUTER SYSTEM; DEVICE FAILURE ANALYSIS; DEVICES; ELECTRONIC NOSE; EQUIPMENT DESIGN; EVALUATION STUDY; INSECT; NERVE CELL NETWORK; ODOR; OLFACTORY RECEPTOR; PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING;

ANIMALS; BIOMIMETICS; COMPUTER SIMULATION; COMPUTER SYSTEMS; ELECTRONIC NOSE; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; INSECTS; MODELS, NEUROLOGICAL; NERVE NET; NEURAL NETWORKS (COMPUTER); RECEPTORS, ODORANT; SIGNAL PROCESSING, COMPUTER-ASSISTED; SMELL;

EID: 84963522612     PISSN: 17483182     EISSN: 17483190     Source Type: Journal    
DOI: 10.1088/1748-3190/11/2/026002     Document Type: Article

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