Add to ORKGFor Gauss-Markov processes the asymptotic behaviors of the first passage time probability density functions through certain time-varying boundaries are determined. Computational results for Wiener, Ornstein-Uhlenbeck and Brownian bridge processes show that for certain large boundaries and for large times excellent asymptotic approximations hold for such densities
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...
Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asympto...
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...
For Gauss-Markov processes the asymptotic behaviors of the first passage time probability density fu...
For a class of Gauss-Markov processes the asymptotic behavior of the first passage time (FPT) probab...
Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asympto...
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...
Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asympto...
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...
For Gauss-Markov processes the asymptotic behaviors of the first passage time probability density fu...
For a class of Gauss-Markov processes the asymptotic behavior of the first passage time (FPT) probab...
Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asympto...
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...
Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asympto...
A new computationally simple, speedy and accurate method is proposed to construct first-passage-time...