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Norms for copulas.

Darsow, William F., Olsen, Elwood T. (1995)

International Journal of Mathematics and Mathematical Sciences

Note on the internal stabilization of stochastic parabolic equations with linearly multiplicative gaussian noise

Viorel Barbu (2013)

ESAIM: Control, Optimisation and Calculus of Variations

The parabolic equations driven by linearly multiplicative Gaussian noise are stabilizable in probability by linear feedback controllers with support in a suitably chosen open subset of the domain. This procedure extends to Navier − Stokes equations with multiplicative noise. The exact controllability is also discussed.

Note on the selection properties of set-valued semimartingales

Mariusz Michta (1996)

Discussiones Mathematicae, Differential Inclusions, Control and Optimization

Set-valued semimartingales are introduced as an extension of the notion of single-valued semimartingales. For such multivalued processes their semimartingale selection properties are investigated.

Note on the variance of the sum of Gaussian functionals

Marek Beśka (2010)

Applicationes Mathematicae

Let ( X i , i = 1 , 2 , . . . ) be a Gaussian sequence with X i N ( 0 , 1 ) for each i and suppose its correlation matrix R = ( ρ i j ) i , j 1 is the matrix of some linear operator R:l₂→ l₂. Then for f i L ² ( μ ) , i=1,2,..., where μ is the standard normal distribution, we estimate the variation of the sum of the Gaussian functionals f i ( X i ) , i=1,2,... .

Note on type II counter problem

Anatolij Dvurečenskij, Genadij A. Ososkov (1984)

Aplikace matematiky

In the paper the authors investigate the explicit form of the joint Laplace transform of the distances between two subsequent moments f particle registrations by the Type II counter (the counter with prolonged dead time), in the general case, and the generating function of the number of particles arriving during the dead time. They give explicit solutions to the complicated integral equations obtained by L. Takács and R. Pyke, respectively. Moreover, they study the geometric behaviour of the distribution...

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