On the modeling of linear system input stochastic processes with given accuracy and reliability
-
Iryna Rozora
und
Mariia Lyzhechko
Abstract
The paper is devoted to the model construction for input stochastic processes of a time-invariant linear system with a real-valued square-integrable impulse response function.
The processes are considered as Gaussian stochastic processes with discrete spectrum.
The response on the system is supposed to be an output process.
We obtain the conditions under which the constructed model approximates a Gaussian stochastic process with given accuracy and reliability in the Banach space
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© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Probability distribution of the life time of a drift-diffusion-reaction process inside a sphere with applications to transient cathodoluminescence imaging
- A quasi-Monte Carlo implementation of the ziggurat method
- On the efficient simulation of the left-tail of the sum of correlated log-normal variates
- Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes
- On the modeling of linear system input stochastic processes with given accuracy and reliability
- Remarks on randomization of quasi-random numbers
- On average dimensions of particle transport estimators
Artikel in diesem Heft
- Frontmatter
- Probability distribution of the life time of a drift-diffusion-reaction process inside a sphere with applications to transient cathodoluminescence imaging
- A quasi-Monte Carlo implementation of the ziggurat method
- On the efficient simulation of the left-tail of the sum of correlated log-normal variates
- Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes
- On the modeling of linear system input stochastic processes with given accuracy and reliability
- Remarks on randomization of quasi-random numbers
- On average dimensions of particle transport estimators
