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Processing of chemical sensor arrays with a biologically inspired model of olfactory coding

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3 Author(s)
Raman, B. ; Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA ; Gutierrez-Galvez, A. ; Gutierrez-Osuna, R.

This paper presents a computational model for chemical sensor arrays inspired by the first two stages in the olfactory pathway: distributed coding with olfactory receptor neurons and chemotopic convergence onto glomerular units. We propose a monotonic concentration-response model that maps conventional sensor-array inputs into a distributed activation pattern across a large population of neuroreceptors. Projection onto glomerular units in the olfactory bulb is then simulated with a self-organizing model of chemotopic convergence. The pattern recognition performance of the model is characterized using a database of odor patterns from an array of temperature modulated chemical sensors. The chemotopic code achieved by the proposed model is shown to improve the signal-to-noise ratio available at the sensor inputs while being consistent with results from neurobiology.

Published in:

Neural Networks, IEEE Transactions on  (Volume:17 ,  Issue: 4 )