Stochastic Evolution Systems: Linear Theory and Applications to Non-linear Filtering: Mathematics and its Applications, cartea 35
Autor B.L. Rozovskiien Limba Engleză Paperback – 27 sep 2012
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Specificații
ISBN-13: 9789401057035
ISBN-10: 9401057036
Pagini: 336
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.47 kg
Ediția:1990
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Mathematics and its Applications
Locul publicării:Dordrecht, Netherlands
ISBN-10: 9401057036
Pagini: 336
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.47 kg
Ediția:1990
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Mathematics and its Applications
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
1
Examples
and
Auxiliary
Results.-
1.0.
Introduction.-
1.1.
Examples
of
Stochastic
Evolution
Systems.-
1.2.
Measurability
and
Integrability
in
Banach
Spaces.-
1.3.
Martingales
in
?1.-
1.4.
Diffusion
Processes.-
2
Stochastic
Integration
in
a
Hilbert
Space.-
2.0.
Introduction.-
2.1.
Martingales
and
Local
Martingales.-
2.2.
Stochastic
Integrals
with
Respect
to
Square
Integrable
Martingale.-
2.3.
Stochastic
Integrable
with
Respect
to
a
Local
Martingale.-
2.4.
An
Energy
Equality
in
a
Rigged
Hilbert
Space.-
3
Linear
Stochastic
Evolution
Systems
in
Hilbert
Spaces.-
3.0.
Introduction.-
3.1.
Coercive
Systems.-
3.2.
Dissipative
Systems.-
3.3.
Uniqueness
and
the
Markov
Property.-
3.4.
The
First
Boundary
Problem
for
Ito’s
Partial
Differential
Equations.-
4
Ito’S
Second
Order
Parabolic
Equations.-
4.0.
Introduction.-
4.1.
The
Cauchy
Problem
for
Superparabolic
Ito’s
Second
Order
Parabolic
Equations.-
4.2.
The
Cauchy
Problem
for
Ito’s
Second
Order
Equations.-
4.3.
The
Forward
Cauchy
Problem
and
the
Backward
One
in
Weighted
Sobolev
Spaces.-
5
Ito’s
Partial
Differential
Equations
and
Diffusion
Processes.-
5.0.
Introduction.-
5.1.
The
Method
of
Stochastic
Characteristics.-
5.2.
Inverse
Diffusion
Processes,
the
Method
of
Variation
of
Constants
and
the
Liouville
Equations.-
5.3.
A
Representation
of
a
Density-valued
Solution.-
6
Filtering
Interpolation
and
Extrapolation
of
Diffusion
Processes.-
6.0.
Introduction.-
6.1.
Bayes’
Formula
and
the
Conditional
Markov
Property.-
6.2.
The
Forward
Filtering
Equation.-
6.3.
The
Backward
Filtering
Equation
Interpolation
and
Extrapolation.-
7
Hypoellipticity
of
Ito’s
Second
Order
Parabolic
Equations.-
7.0.
Introduction.-
7.1.
Measure-valued
Solution
and
Hypoellipticity
under
Generalized
Hörmander’s
Condition.-
7.2.
The
Filtering
Transition
Density
and
a
Fundamental
Solution
of
the
Filtering
Equation
in
Hypoelliptic
and
Superparabolic
Cases.-
Notes.-
References.