Evolutionary computation enhancement of olfactory system model

Geza Szekely, Mary Lou Padgett, Gerry Dozier

Research output: Paper

1 Citation (Scopus)

Abstract

Recent electron microscopy work on rat olfactory system anatomy suggests a structural basis for grouping input stimuli before processing to classify odors. For a simulated nose, the number of inputs per group is a design parameter. Previous results indicate that improvements in classification accuracy can be made by grouping inputs, but such an increase is expensive in terms of hardware and speed. This paper demonstrates that use of evolutionary algorithms (EA) to tune PCNN factoring parameters improves accuracy significantly, with a reasonable processing time, so an increase in inputs per group is not needed.

Original languageEnglish
Pages503-510
Number of pages8
DOIs
Publication statusPublished - jan. 1 1999
Event1999 Congress on Evolutionary Computation, CEC 1999 - Washington, DC, United States
Duration: júl. 6 1999júl. 9 1999

Other

Other1999 Congress on Evolutionary Computation, CEC 1999
CountryUnited States
CityWashington, DC
Period7/6/997/9/99

ASJC Scopus subject areas

  • Computational Mathematics

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    Szekely, G., Padgett, M. L., & Dozier, G. (1999). Evolutionary computation enhancement of olfactory system model. 503-510. Paper presented at 1999 Congress on Evolutionary Computation, CEC 1999, Washington, DC, United States. https://doi.org/10.1109/CEC.1999.781974