White Noise Methods for Anticipating Stochastic Differential Equations

This dissertation focuses on linear stochastic differential equations of anticipating type. Owing to the lack of a theory of differentiation for random processes, the said differential equations are appropriately understood and studied as anticipating stochastic integral equations. The unfolding wo...

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Main Author:	Esunge, Julius
Other Authors:	Charles Monlezun
Format:	Others
Language:	en
Published:	LSU 2009
Subjects:	Mathematics
Online Access:	http://etd.lsu.edu/docs/available/etd-07062009-094329/

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spelling	ndltd-LSU-oai-etd.lsu.edu-etd-07062009-0943292013-01-07T22:52:16Z White Noise Methods for Anticipating Stochastic Differential Equations Esunge, Julius Mathematics This dissertation focuses on linear stochastic differential equations of anticipating type. Owing to the lack of a theory of differentiation for random processes, the said differential equations are appropriately understood and studied as anticipating stochastic integral equations. The unfolding work considers equations in which anticipation arises either from the initial condition or the integrand. In this regard, the techniques of white noise analysis are applied to such equations. In particular, by using the Hitsuda-Skorokhod integral which nicely extends the It integral to anticipating integrands, we then apply the S-transform from white noise analysis to study this new equation. Charles Monlezun Ambar Sengupta Padmanabhan Sundar Stephen Shipman Robert Perlis Hui-Hsiung Kuo LSU 2009-07-06 text application/pdf http://etd.lsu.edu/docs/available/etd-07062009-094329/ http://etd.lsu.edu/docs/available/etd-07062009-094329/ en unrestricted I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.
collection	NDLTD
language	en
format	Others
sources	NDLTD
topic	Mathematics
spellingShingle	Mathematics Esunge, Julius White Noise Methods for Anticipating Stochastic Differential Equations
description	This dissertation focuses on linear stochastic differential equations of anticipating type. Owing to the lack of a theory of differentiation for random processes, the said differential equations are appropriately understood and studied as anticipating stochastic integral equations. The unfolding work considers equations in which anticipation arises either from the initial condition or the integrand. In this regard, the techniques of white noise analysis are applied to such equations. In particular, by using the Hitsuda-Skorokhod integral which nicely extends the It integral to anticipating integrands, we then apply the S-transform from white noise analysis to study this new equation.
author2	Charles Monlezun
author_facet	Charles Monlezun Esunge, Julius
author	Esunge, Julius
author_sort	Esunge, Julius
title	White Noise Methods for Anticipating Stochastic Differential Equations
title_short	White Noise Methods for Anticipating Stochastic Differential Equations
title_full	White Noise Methods for Anticipating Stochastic Differential Equations
title_fullStr	White Noise Methods for Anticipating Stochastic Differential Equations
title_full_unstemmed	White Noise Methods for Anticipating Stochastic Differential Equations
title_sort	white noise methods for anticipating stochastic differential equations
publisher	LSU
publishDate	2009
url	http://etd.lsu.edu/docs/available/etd-07062009-094329/
work_keys_str_mv	AT esungejulius whitenoisemethodsforanticipatingstochasticdifferentialequations
_version_	1716477782851059712

White Noise Methods for Anticipating Stochastic Differential Equations

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