Hücresel yapay sinir aǧi tabanli olfaktif bulb modelinin bir koku siniflandirma probleminde en i̇yi sensör sicakliǧin bulunmasi i̇çin kullanilmasi

Translated title of the contribution: Using a cellular neural network based olfactory bulb model for choosing the best sensor temperature for an odor classification problem

T. Ayhan*, M. K. Muezzinoǧlu, A. Vergara, M. E. Yalçin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a part of mamal olfaction system, olfactory bulb, is modelled by a Cellular Ceural Network and the performance of the model in an odor classification problem is evaluated for different sensör temperatures in order to figure out in which sensör temperature the most distinguishable data is recorded.The relevant probem in odor classification task is the slowy changing time response of the odor sensors and the model presented in this work is a structure that can be used to speed up odor processing.

Translated title of the contributionUsing a cellular neural network based olfactory bulb model for choosing the best sensor temperature for an odor classification problem
Original languageTurkish
Title of host publicationSIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference
Pages578-581
Number of pages4
DOIs
Publication statusPublished - 2010
Event18th IEEE Signal Processing and Communications Applications Conference, SIU 2010 - Diyarbakir, Turkey
Duration: 22 Apr 201024 Apr 2010

Publication series

NameSIU 2010 - IEEE 18th Signal Processing and Communications Applications Conference

Conference

Conference18th IEEE Signal Processing and Communications Applications Conference, SIU 2010
Country/TerritoryTurkey
CityDiyarbakir
Period22/04/1024/04/10

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