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<P><FONT color=#800080>A Concise Course on Stochastic Partial Differential Equations (Lecture Notes in Mathematics) </FONT></P>
<P><IMG src="http://ec1.images-amazon.com/images/I/41gN6i+OeCL.jpg" border=0></P>
<P>By Claudia Prév&ocirc;t, Michael R&ouml;ckner, </P>
<P><BR>Publisher: Springer <BR>Number Of Pages: 148 <BR>Publication Date: 2007-07 <BR>Sales Rank: 3606459 <BR>ISBN / ASIN: 3540707808 <BR>EAN: 9783540707806 <BR>Binding: Paperback <BR>Manufacturer: Springer <BR>Studio: Springer </P>
<P>Book Description: </P>
<P><BR>These lectures concentrate on (nonlinear) stochastic partial differential equations (SPDE) of evolutionary type. All kinds of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. To keep the technicalities minimal we confine ourselves to the case where the noise term is given by a stochastic integral w.r.t. a cylindrical Wiener process.But all results can be easilyread.freeduan.com generalized to SPDE with more general noises such as, for instance, stochastic integral w.r.t. a continuous local martingale.There are basically three approaches to analyze SPDE: the "martingale measure approach", the "mild solution approach” and the "variational approach". The purpose of these notes is to give a concise and as self-contained as possible an introduction to the "variational approach”. A large part of necessary background material, such as definitions and results from the theory of Hilbert spaces, are included in appendices.<BR></P>
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