By Thomas Nowotny (auth.), Agustín Gutiérrez, Santiago Marco (eds.)
This quantity provides a suite of study advances in biologically encouraged sign processing for chemical sensing. The olfactory process, and the gustatory approach to a minor volume, has been taken within the final many years as a resource of proposal to increase synthetic sensing structures. The functionality of this organic method outperforms in lots of elements that in their synthetic counterpart. hence, the target of researchers during this box is to appreciate and catch these positive aspects that make the olfactory procedure in particular fitted to the processing of chemical details. the popularity of odors through the olfactory process involves a couple of sign processing capabilities reminiscent of preprocessing, dimensionality aid, distinction enhancement, and class. utilizing mathematical types to imitate the structure of the olfactory procedure, those processing services could be utilized to chemical sensor indications. This e-book offers a few historical past at the olfactory method together with a overview on details processing within the insect olfactory process besides a proposed sign processing structure in line with the mammalian cortex. It additionally presents a few bio-inspired methods to strategy chemical sensor signs comparable to an olfactory mucosa to enhance smell separation and a version of olfactory receptor neuron convergence to correlate sensor responses to an smell and his organoleptic homes.
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Additional info for Biologically Inspired Signal Processing for Chemical Sensing
For each generated input pattern . 9) Here we sum over all groups and all units in each group where is the activation value of unit i. 10) In a classification task, the unit with the highest output is taken as the classification result. 38 A. Lansner, S. Benjaminsson, and C. 4 Data Sets In this study we used two different datasets, one of activation patterns from rat olfactory bulb and one of isolated handwritten digits. Rat Olfactory Bulb Activation Patterns The olfactory bulb activation data of Leon and Johnson was used as one of the evaluation data sets (Leon and Johnson).
More realistic model of the olfactory system of insects. e. each ball represents 10 neurons). The eKCs are connected all-to-all with mutual inhibition. The additional pathway involving lateral horn interneurons provides global inhibition on the KCs. (Modified from Nowotny et al. 2005). 20 T. Nowotny Fig. 9. Pairwise distances of activity patterns in the different stages (distances normalized between 0 and 1). Here, the system experiences 10 input classes of 10 patterns each. , input 1 to 10 is class 1 etc.
E. Kaissling of molecules passing an area equal to the antennal outline area that was adsorbed on these antennae was 32% (Kanaujia and Kaissling 1985). Thus we may conclude for both species of moths that from the air passing the antenna itself all pheromone molecules were caught. In males of Bombyx mori (Steinbrecht and Kasang 1972) and Antheraea polyphemus (Kanaujia and Kaissling 1985) we determined the fraction of molecules caught by the antenna that was adsorbed on the long olfactory hairs (sensilla trichodea).