Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations

Some microbial systems exhibit sustained oscillations under certain conditions. The maintenance and the suppression of oscillations are both important in different situations. While oscillations are clearly identifiable in small bioreactors, the influx of noise fuzzifies the oscillations in larger v...

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Main Author: Pratap Patnaik
Format: Article
Language:English
Published: Academic Publishing House 2006-04-01
Series:Bioautomation
Subjects:
Online Access:http://www.clbme.bas.bg/bioautomation/2006/vol_4.1/files/4_3.3.pdf
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author Pratap Patnaik
author_facet Pratap Patnaik
author_sort Pratap Patnaik
collection DOAJ
description Some microbial systems exhibit sustained oscillations under certain conditions. The maintenance and the suppression of oscillations are both important in different situations. While oscillations are clearly identifiable in small bioreactors, the influx of noise fuzzifies the oscillations in larger vessels. So, noise-filtering devices are employed to recover clear oscillating profiles. Recent work has shown that an auto-associative (AA) neural network is a better than standard algorithmic filters. In this study, nine neural network designs are compared for their ability to filter Gaussian noise in the substrate inflow rate of a continuous fermentation containing Saccharomyces cerevisiae. While the AA network is the best overall, specific performance criteria favor other designs. Thus the choice of a neural filter depends on the evaluation criterion, which is guided by the application.
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spelling doaj.art-adf6f67f6d164d97925986b28306a95b2022-12-22T01:09:46ZengAcademic Publishing HouseBioautomation1313-261X1312-451X2006-04-01414556Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial FermentationsPratap PatnaikSome microbial systems exhibit sustained oscillations under certain conditions. The maintenance and the suppression of oscillations are both important in different situations. While oscillations are clearly identifiable in small bioreactors, the influx of noise fuzzifies the oscillations in larger vessels. So, noise-filtering devices are employed to recover clear oscillating profiles. Recent work has shown that an auto-associative (AA) neural network is a better than standard algorithmic filters. In this study, nine neural network designs are compared for their ability to filter Gaussian noise in the substrate inflow rate of a continuous fermentation containing Saccharomyces cerevisiae. While the AA network is the best overall, specific performance criteria favor other designs. Thus the choice of a neural filter depends on the evaluation criterion, which is guided by the application.http://www.clbme.bas.bg/bioautomation/2006/vol_4.1/files/4_3.3.pdf Microbial oscillationsSaccharomyces cerevisiaeBioreactorNoise inflowNeural filters
spellingShingle Pratap Patnaik
Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
Bioautomation
Microbial oscillations
Saccharomyces cerevisiae
Bioreactor
Noise inflow
Neural filters
title Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
title_full Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
title_fullStr Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
title_full_unstemmed Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
title_short Neural Network Configurations for Filtering of Feed Stream Noise from Oscillating Continuous Microbial Fermentations
title_sort neural network configurations for filtering of feed stream noise from oscillating continuous microbial fermentations
topic Microbial oscillations
Saccharomyces cerevisiae
Bioreactor
Noise inflow
Neural filters
url http://www.clbme.bas.bg/bioautomation/2006/vol_4.1/files/4_3.3.pdf
work_keys_str_mv AT pratappatnaik neuralnetworkconfigurationsforfilteringoffeedstreamnoisefromoscillatingcontinuousmicrobialfermentations