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March  2013, 18(2): 453-465. doi: 10.3934/dcdsb.2013.18.453

Asymptotic behaviour of random tridiagonal Markov chains in biological applications

1. 

Institut für Mathematik, Goethe Universität, D-60054 Frankfurt am Main

2. 

Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoj Karetny lane 19, Moscow 127994 GSP-4

Received  February 2011 Revised  May 2012 Published  November 2012

Discrete-time discrete-state random Markov chains with a tridiagonal generator are shown to have a random attractor consisting of singleton subsets, essentially a random path, in the simplex of probability vectors. The proof uses the Hilbert projection metric and the fact that the linear cocycle generated by the Markov chain is a uniformly contractive mapping of the positive cone into itself. The proof does not involve probabilistic properties of the sample path $\omega$ and is thus equally valid in the nonautonomous deterministic context of Markov chains with, say, periodically varying transitions probabilities, in which case the attractor is a periodic path.
Citation: Peter E. Kloeden, Victor Kozyakin. Asymptotic behaviour of random tridiagonal Markov chains in biological applications. Discrete & Continuous Dynamical Systems - B, 2013, 18 (2) : 453-465. doi: 10.3934/dcdsb.2013.18.453
References:
[1]

L. J. S. Allen, "An Introduction to Stochastic Processes with Applications to Biology,", CRC Press, (2011). Google Scholar

[2]

L. Arnold, "Random Synamical Systems,", Springer Monographs in Mathematics, (1998). Google Scholar

[3]

E. Asarin, P. Diamond, I. Fomenko et al., Chaotic phenomena in desynchronized systems and stability analysis,, Comput. Math. Appl., 25 (1993), 81. doi: 10.1016/0898-1221(93)90214-G. Google Scholar

[4]

J.-P. Aubin and H. Frankowska, "Set-valued Analysis,", Modern Birkhäuser Classics, (2009). Google Scholar

[5]

M. F. Barnsley, A. Vince and D. C. Wilson, Real projective iterated function systems,, ArXiv.org e-Print archive, (). Google Scholar

[6]

P. J. Bushell, Hilbert's metric and positive contraction mappings in a Banach space,, Arch. Rational Mech. Anal., 52 (1973), 330. Google Scholar

[7]

D. N. Cheban, P. E. Kloeden and B. Schmalfuß, The relationship between pullback, forward and global attractors of nonautonomous dynamical systems,, Nonlinear Dyn. Syst. Theory, 2 (2002), 125. Google Scholar

[8]

I. Chueshov, "Monotone Random Systems Theory and Applications,", 1779 of Lecture Notes in Mathematics, 1779 (2002). Google Scholar

[9]

I. Chueshov and M. Scheutzow, On the structure of attractors and invariant measures for a class of monotone random systems,, Dyn. Syst., 19 (2004), 127. doi: 10.1080/1468936042000207792. Google Scholar

[10]

H. Cohn, Products of stochastic matrices and applications,, Internat. J. Math. Math. Sci., 12 (1989), 209. doi: 10.1155/S0161171289000268. Google Scholar

[11]

D. J. Hartfiel, "Markov Set-Chains,", 1695 of Lecture Notes in Mathematics, 1695 (1998). Google Scholar

[12]

D. J. Hartfiel, "Nonhomogeneous Matrix Products,", World Scientific Publishing Co. Inc., (2002). Google Scholar

[13]

A. E. Hutzenthaler, "Mathematical Models for Cell-Cell Coomunication on Different Time Scales,", Ph.D. thesis, (2009). Google Scholar

[14]

P. Imkeller and P. Kloeden, On the computation of invariant measures in random dynamical systems,, Stoch. Dyn., 3 (2003), 247. doi: 10.1142/S0219493703000711. Google Scholar

[15]

P. E. Kloeden and M. Rasmussen, "Nonautonomous Dynamical Systems,", 176 of Mathematical Surveys and Monographs, 176 (2011). Google Scholar

[16]

M. A. Krasnosel$'$skij, J. A. Lifshits and A. V. Sobolev, "Positive Linear Systems,", 5 of Sigma Series in Applied Mathematics, 5 (1989). Google Scholar

[17]

A. Leizarowitz, On infinite products of stochastic matrices,, Linear Algebra Appl., 168 (1992), 189. doi: 10.1016/0024-3795(92)90294-K. Google Scholar

[18]

M. Neumann and H. Schneider, The convergence of general products of matrices and the weak ergodicity of Markov chains,, Linear Algebra Appl., 287 (1999), 307. doi: 10.1016/S0024-3795(98)10196-9. Google Scholar

[19]

B. Noble and J. W. Daniel, "Applied Linear Algebra,", Prentice-Hall Inc., (1977). Google Scholar

[20]

B. S. Thomson, J. B. Bruckner and A. M. Bruckner, "Elementary Real Analysis,", www.classicalrealanalysis.com, (2008). Google Scholar

[21]

D. Wodarz and N. Komarova, "Computational Biology of Cancer: Lecture Notes and Mathematical Modeling,", World Scientific Publishing Co. Pte. Ltd., (2005). Google Scholar

[22]

J. Wolfowitz, Products of indecomposable, aperiodic, stochastic matrices,, Proc. Amer. Math. Soc., 14 (1963), 733. Google Scholar

show all references

References:
[1]

L. J. S. Allen, "An Introduction to Stochastic Processes with Applications to Biology,", CRC Press, (2011). Google Scholar

[2]

L. Arnold, "Random Synamical Systems,", Springer Monographs in Mathematics, (1998). Google Scholar

[3]

E. Asarin, P. Diamond, I. Fomenko et al., Chaotic phenomena in desynchronized systems and stability analysis,, Comput. Math. Appl., 25 (1993), 81. doi: 10.1016/0898-1221(93)90214-G. Google Scholar

[4]

J.-P. Aubin and H. Frankowska, "Set-valued Analysis,", Modern Birkhäuser Classics, (2009). Google Scholar

[5]

M. F. Barnsley, A. Vince and D. C. Wilson, Real projective iterated function systems,, ArXiv.org e-Print archive, (). Google Scholar

[6]

P. J. Bushell, Hilbert's metric and positive contraction mappings in a Banach space,, Arch. Rational Mech. Anal., 52 (1973), 330. Google Scholar

[7]

D. N. Cheban, P. E. Kloeden and B. Schmalfuß, The relationship between pullback, forward and global attractors of nonautonomous dynamical systems,, Nonlinear Dyn. Syst. Theory, 2 (2002), 125. Google Scholar

[8]

I. Chueshov, "Monotone Random Systems Theory and Applications,", 1779 of Lecture Notes in Mathematics, 1779 (2002). Google Scholar

[9]

I. Chueshov and M. Scheutzow, On the structure of attractors and invariant measures for a class of monotone random systems,, Dyn. Syst., 19 (2004), 127. doi: 10.1080/1468936042000207792. Google Scholar

[10]

H. Cohn, Products of stochastic matrices and applications,, Internat. J. Math. Math. Sci., 12 (1989), 209. doi: 10.1155/S0161171289000268. Google Scholar

[11]

D. J. Hartfiel, "Markov Set-Chains,", 1695 of Lecture Notes in Mathematics, 1695 (1998). Google Scholar

[12]

D. J. Hartfiel, "Nonhomogeneous Matrix Products,", World Scientific Publishing Co. Inc., (2002). Google Scholar

[13]

A. E. Hutzenthaler, "Mathematical Models for Cell-Cell Coomunication on Different Time Scales,", Ph.D. thesis, (2009). Google Scholar

[14]

P. Imkeller and P. Kloeden, On the computation of invariant measures in random dynamical systems,, Stoch. Dyn., 3 (2003), 247. doi: 10.1142/S0219493703000711. Google Scholar

[15]

P. E. Kloeden and M. Rasmussen, "Nonautonomous Dynamical Systems,", 176 of Mathematical Surveys and Monographs, 176 (2011). Google Scholar

[16]

M. A. Krasnosel$'$skij, J. A. Lifshits and A. V. Sobolev, "Positive Linear Systems,", 5 of Sigma Series in Applied Mathematics, 5 (1989). Google Scholar

[17]

A. Leizarowitz, On infinite products of stochastic matrices,, Linear Algebra Appl., 168 (1992), 189. doi: 10.1016/0024-3795(92)90294-K. Google Scholar

[18]

M. Neumann and H. Schneider, The convergence of general products of matrices and the weak ergodicity of Markov chains,, Linear Algebra Appl., 287 (1999), 307. doi: 10.1016/S0024-3795(98)10196-9. Google Scholar

[19]

B. Noble and J. W. Daniel, "Applied Linear Algebra,", Prentice-Hall Inc., (1977). Google Scholar

[20]

B. S. Thomson, J. B. Bruckner and A. M. Bruckner, "Elementary Real Analysis,", www.classicalrealanalysis.com, (2008). Google Scholar

[21]

D. Wodarz and N. Komarova, "Computational Biology of Cancer: Lecture Notes and Mathematical Modeling,", World Scientific Publishing Co. Pte. Ltd., (2005). Google Scholar

[22]

J. Wolfowitz, Products of indecomposable, aperiodic, stochastic matrices,, Proc. Amer. Math. Soc., 14 (1963), 733. Google Scholar

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