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Yosida Approximations of Stochastic Differential Equations in Infinite Dimensions and Applications (Paperback, Softcover reprint of the original 1st ed. 2016)
Loot Price: R4,445
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Yosida Approximations of Stochastic Differential Equations in Infinite Dimensions and Applications (Paperback, Softcover reprint of the original 1st ed. 2016)
Series: Probability Theory and Stochastic Modelling, 79
Expected to ship within 10 - 15 working days
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This research monograph brings together, for the first time, the
varied literature on Yosida approximations of stochastic
differential equations (SDEs) in infinite dimensions and their
applications into a single cohesive work. The author provides a
clear and systematic introduction to the Yosida approximation
method and justifies its power by presenting its applications in
some practical topics such as stochastic stability and stochastic
optimal control. The theory assimilated spans more than 35 years of
mathematics, but is developed slowly and methodically in digestible
pieces. The book begins with a motivational chapter that introduces
the reader to several different models that play recurring roles
throughout the book as the theory is unfolded, and invites readers
from different disciplines to see immediately that the effort
required to work through the theory that follows is worthwhile.
From there, the author presents the necessary prerequisite
material, and then launches the reader into the main discussion of
the monograph, namely, Yosida approximations of SDEs, Yosida
approximations of SDEs with Poisson jumps, and their applications.
Most of the results considered in the main chapters appear for the
first time in a book form, and contain illustrative examples on
stochastic partial differential equations. The key steps are
included in all proofs, especially the various estimates, which
help the reader to get a true feel for the theory of Yosida
approximations and their use. This work is intended for researchers
and graduate students in mathematics specializing in probability
theory and will appeal to numerical analysts, engineers, physicists
and practitioners in finance who want to apply the theory of
stochastic evolution equations. Since the approach is based mainly
in semigroup theory, it is amenable to a wide audience including
non-specialists in stochastic processes.
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