Type of Document	Dissertation
Author	Esunge, Julius
URN	etd-07062009-094329
Title	White Noise Methods for Anticipating Stochastic Differential Equations
Degree	Doctor of Philosophy (Ph.D.)
Department	Mathematics
Advisory Committee	Advisor Name Title Hui-Hsiung Kuo Committee Chair Ambar Sengupta Committee Member Padmanabhan Sundar Committee Member Robert Perlis Committee Member Stephen Shipman Committee Member Charles Monlezun Dean's Representative
Keywords	White Noise Anticipating Stochastic Differential Equations
Date of Defense	2009-06-10
Availability	unrestricted
Abstract 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.
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