Agustin Gutierrez-Galvez

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This article presents a sensor excitation and signal processing approach that combines temperature modulation and transient analysis to enhance the selectivity and sensitivity of metal-oxide gas sensors. A staircase waveform is applied to the sensor heater to extract transient information from multiple operating temperatures. Four different transient(More)
The olfactory bulb is able to enhance the contrast between odor representations through a combination of excitatory and inhibitory circuits. Inspired by this mechanism, we propose a new Hebbian/anti-Hebbian learning rule to increase the separability of sensor-array patterns in a neurodynamics model of the olfactory system: the KIII. In the proposed learning(More)
This paper presents a novel combination of chemical sensors and the KIII model for simulating mixture perception with a habituation process triggered by local activity. Stimuli are generated by partitioning feature space with labeled lines. Pattern completion is demonstrated through coherent oscillations across granule populations using experimental odor(More)
This article presents an alternative phase coding mechanism for Freeman's KIII model of population neurodynamics. Motivated by experimental evidence that supports the existence of a neural code based on synchronous oscillations, we propose an analogy between synchronization in neural populations and phase locking in KIII channels. An efficient method is(More)
We propose a biologically inspired model of olfactory processing for chemosensor arrays. The model captures three functions in the early olfactory pathway: chemotopic convergence of receptor neurons onto the olfactory bulb, center on-off surround lateral interactions, and adaptation to sustained stimuli. The projection of ORNs onto glomerular units is(More)
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(More)
In an effort to deepen our understanding of mammalian olfactory coding, we have used an objective method to analyze a large set of odorant-evoked activity maps collected systematically across the rat olfactory bulb to determine whether such an approach could identify specific glomerular regions that are activated by related odorants. To that end, we(More)
Inspired by the habituation process in the olfactory system, this article presents an approach for analyzing electronic-nose data using Freeman's KIII neurodynamics model. In order to ensure the additivity of patterns from odor mixtures, input data from a gas sensor array is first processed with a family of discriminant functions that yield an orthogonal(More)
We present a methodology based on Information theory tools to optimize the operating temperatures of metal-oxide (MOX) gas sensor arrays and maximize the ability of the system in odor discrimination tasks. We have demonstrated the feasibility of the method by optimizing the temperatures of a four-sensor array for an effective discrimination of four(More)
Inspired by the ability of the olfactory bulb to enhance the contrast between odor representations , we propose a new hebbian learning rule that is able to increase the separability of odor patterns from gas sensor arrays. The proposed learning rule employs a hebbian term to build associations within odors and an anti-hebbian term to reduce correlated(More)