Quantitative ergodicity for some switched dynamical systems
We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd \times E where E is a finite set. The continuous component evolves according to a smooth vector field that switches at the jump times of the discrete coordinate. The j...
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| creator | Benaïm, Michel Stéphane Le Borgne Malrieu, Florent Pierre-André Zitt |
| description | We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd \times E where E is a finite set. The continuous component evolves according to a smooth vector field that switches at the jump times of the discrete coordinate. The jump rates may depend on the whole position of the process. Under regularity assumptions on the jump rates and stability conditions for the vector fields we provide explicit exponential upper bounds for the convergence to equilibrium in terms of Wasserstein distances. As an example, we obtain convergence results for a stochastic version of the Morris-Lecar model of neurobiology. |
| doi_str_mv | 10.48550/arxiv.1204.1922 |
| format | Article |
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| subjects | Convergence Economic models Fields (mathematics) Markov analysis Markov processes Mathematics - Probability Neurosciences Switches Upper bounds |
| title | Quantitative ergodicity for some switched dynamical systems |
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