Biologically Inspired Signal Processing for Chemical Sensing by Thomas Nowotny (auth.), Agustín Gutiérrez, Santiago Marco

By Thomas Nowotny (auth.), Agustín Gutiérrez, Santiago Marco (eds.)

This quantity offers a set of analysis advances in biologically encouraged sign processing for chemical sensing. The olfactory approach, and the gustatory method to a minor quantity, has been taken within the final many years as a resource of suggestion to boost man made sensing platforms. The functionality of this organic process outperforms in lots of points that in their synthetic counterpart. hence, the aim of researchers during this box is to appreciate and seize these beneficial properties that make the olfactory method specially fitted to the processing of chemical info. the popularity of odors via the olfactory method includes a couple of sign processing capabilities akin to preprocessing, dimensionality aid, distinction enhancement, and class. utilizing mathematical types to imitate the structure of the olfactory method, those processing features may be utilized to chemical sensor indications. This publication offers a few heritage at the olfactory process together with a evaluation on info processing within the insect olfactory method in addition to a proposed sign processing structure in keeping with the mammalian cortex. It additionally offers a few bio-inspired methods to procedure chemical sensor signs reminiscent of an olfactory mucosa to enhance scent separation and a version of olfactory receptor neuron convergence to correlate sensor responses to an scent and his organoleptic homes.

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12. Differences in the integrated activity of KCs. Black circles symbolize KCs that are more active in response to an activity pattern sequence A, C, B than to A, B, C, light grey circles symbolize KCs which activity is the same for both and dark grey circles are KCs which respond more to A, B, C. (Modified from (Nowotny et al. 2003)). were connected by slow excitatory connections with the topology of a hexagonal lattice according to the earlier experimental findings (Leitch and Laurent 1996). 12).

A1) where the conditional probability is given by ⎛N ⎞ k N −k P (nKC = k | nPN = l ) = ⎜⎜ KC ⎟⎟ pKC (l ) (1 − pKC (l )) KC . A2) pKC (l ) denotes the conditional probability for a single KC to fire given l PNs are active, l ⎛l⎞ j l− j pKC (l ) = ∑ ⎜⎜ ⎟⎟ pPN → KC (1 − pPN → KC ) . A3) For a more explicit explanation see (Nowotny and Huerta 2003). B1) K K x , x ′,C where the triangular brackets denote the expectation value with respect to the product K K measure for inputs x , x ′ and connectivity C .

2004). A similar observation of reproducibility across animals has been made on the activity patterns in the olfactory cortex of rats (Zou et al. 2005). In the MBs, the picture presents itself slightly differently. The studies in adult Drosophila find a lack of stereotypy in the branching patterns of PNs in the MB calyx (Wong et al. 2002; Marin et al. 2002) and in a recent study of the olfactory system in Drosophila larvae the authors refer to outright “potential random patterns of connectivity in the MB calyx” (Masuda-Nakagawa et al.

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