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
Link To Document :
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