DocumentCode
699637
Title
Stochastic simulation and parameter estimation of first order chemical reactions
Author
De Cock, Katrien ; Xueying Zhang ; Bugallo, Monica F. ; Djuric, Petar M.
Author_Institution
Dept. of Electr. & Comput. Eng., Stony Brook Univ., Stony Brook, NY, USA
fYear
2004
fDate
6-10 Sept. 2004
Firstpage
1111
Lastpage
1114
Abstract
In this paper, we present fast stochastic simulation methods for the class of first order chemical reactions. The methods are based on the exact distributions for the number of molecules or their Gaussian approximations. Furthermore, using the adopted models, we develop parameter estimation methods for the reaction rates. Although we only discuss two basic reactions, the single channel and reversible first order reactions, the obtained results can be applied to more complex cases.
Keywords
approximation theory; chemical reactions; parameter estimation; reaction kinetics; stochastic processes; Gaussian approximations; adopted models; fast stochastic simulation methods; first order chemical reactions; parameter estimation methods; reaction rates; reversible first order reactions; single channel reactions; Abstracts; Approximation methods; Artificial neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2004 12th European
Conference_Location
Vienna
Print_ISBN
978-320-0001-65-7
Type
conf
Filename
7080167
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