Neural network based algorithm of preliminary data analysis: Application to fluorescence and ESR spectroscopy

P. V. Nazarov*, A. A. Kavalenka, K. U. Makarava, V. M. Lutkovski, V. V. Apanasovich

*Corresponding author for this work

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

Abstract

The fluorescence and electron spin resonance (ESR) spectroscopy are very important experimental tools for studying complex biomolecular objects and systems. The analysis of spectroscopic experimental data is often conducted by means of fitting using an analytical or a simulation models. For the successful performance of the fitting operation, an adequate model should be selected and good initial estimations of its parameters should be made. We propose to use artificial neural networks (ANNs) to recognise the appropriate model and to produce initial estimations of model's parameters before fitting.

Original languageEnglish
Title of host publicationMS'2004 - International Conference on Modelling and Simulation
EditorsV. Krasnoproshin, J.G. Aluja
Pages130-134
Number of pages5
Publication statusPublished - 2004
Externally publishedYes
EventMS'2004 - International Conference on Modelling and Simulation - Minsk, Belarus
Duration: 27 Apr 200429 Apr 2004

Publication series

NameMS'2004 - International Conference on Modelling and Simulation

Conference

ConferenceMS'2004 - International Conference on Modelling and Simulation
Country/TerritoryBelarus
CityMinsk
Period27/04/0429/04/04

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