Overview

The1989SeminaronStochasticProcesseswasheldattheUniversityof CaliforniaatSanDiegoonMarch30,31andApril1,Hl89. Thiswastheninth inanannualseriesofmeetingswhichprovideresearcherswiththeopportunity todiscusscurrentworkonstochasticprocessesinaninformalandenjoyableat- mosphere. PreviousseminarswereheldatPrincetonUniversity,Northwestern University,theUniversityofFloridaandtheUniversityofVirginia. Theseminar hasgrownovertheyears,withatotalofseventy-fiveparticipantsin1989. Fol- lowingthesuccessfulformatofpreviousyears,therewerefiveinvitedlectures, deliveredby K. L. Chung,D. Dawson, R. Durrett,N. IkedaandT. Lyons,with theremainderoftimebeingdevotedtostructured,butlessformal,discussionson currentworkandproblems. Severalsmallergroupsalsoheldworkshopsessions onspecifictopicssuchas:mper-processes,diffusionsonfractalsandHarnack inequalities. Theparticipant. s'interestandenthusiasmcreatedalivelyandstim- ulatingcnvironmentfortheseminar. Asampleoftheresearchdiscussedthereis containedinthisvolume. Thc1989SeminarwasmadepossiblebythesupportoftheNationalScience Foundation,theNationalSecurityAgencyandtheUniversityofCaliforniaatSan Diego. \Yeextendourthankstothem,andtothepublishcrBirkhauserBoston, fortheirsupportandencouragemcnt. Finally,thanksgotoLynn\,yilliamsforher cheerfulassistancewiththeseminarorganizationandproductionofthisvolume. P. J. Fitzsimmons R. J. Williams LaJolla,1989 LISTOFPARTICIPANTS P. Arzberger M. Emery E. Perkins J. Pitman B. Atkinson S. N. Evans L. Pitt J. Azema N. Falkner M. Bachman P. Fitzsimmons A. O. Pittenger Z. Pop-Stojanovic M. Barlow R. K. Getoor R. Bass J. Glover S. Port C. Bezuidenhout H. Heyer P. Protter R. Blumenthal K. Hoffmann K. M. Rao G. Brosamler J. Horowitz J. Rosen C. Burdzy P. Hsu T. Salisbury D. Burkholder N. Ikeda M. J. Sharpe H. Cai O. Kallenberg C. T. Shih R. Carmona F. Knight A. Sznitman W. Chen-Masters Y. Kwon M. Taksar K. L. Chung T. Kurtz L. Taylor E. Cinlar T. Liggett S. J. Taylor M. Cranston T. Lyons G. Terdik R. Dalang P. March E. Toby R. DanteDeBlassie M. Marcus R. Tribe R. Darling P. McGill J. Walsh D. Dawson T. Mountford J. Watkins J. Deuschel B. Oksendal S. Weinryb N. Dinculeanu V. Papanicolaou R. Williams R. Durrett R. Pemantle Z. Zhao E. B. Dynkin M. Penrose W. Zheng TABLEOFCONTENTS R. F. BASS Aprobabilisticproofoftheboundary 1 and K. BURDZY Harnackprinciple J. -D. DEUSCHEL LogarithmicSobolevinequalitiesof 17 symmetricdiffusions S. N. EVANS RescalingthevacancyofaBoolean coverageprocess 23 TheBlumenthal-Getoor-McKean P. J. FITZSIMMONS, R. K. GETOOR Theoremrevisited 35 andM. J. SHARPE P. J. FITZSIMMONS Localtimes,occupationtimes,andthe Lebesguemeasureoftherangeofa andS. C.

Full Product Details

Author:   E. Cinlar
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1990
Volume:   18
Dimensions:   Width: 15.20cm , Height: 1.20cm , Length: 22.90cm
Weight:   0.340kg
ISBN:  

9781461280316

ISBN 10:   1461280311
Pages:   216
Publication Date:   17 September 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

A probabilistic proof of the boundary Harnack principle.- Logarithmic Sobolev inequalities of symmetric diffusions.- Rescaling the vacancy of a Boolean coverage process.- The Blumenthal-Getoor-McKean Theorem revisited.- Local times, occupation times, and the Lebesgue measure of the range of a Levy process.- Martingale problems associated with the Boltzmann equation.- Probabilistic methods in differential geometry.- Probabilistic methods in Schrödinger equations.- Stochastic variational principle of Schrödinger processes.- The high contact principle in optimal stopping and stochastic waves.- Continuity of solutions of Schrödinger equation.- Stationary solutions for bilinear systems with constant coefficients.- Gaugeability for unbounded domains.- Correction to: Some formulas for the energy functional of a Markov process.

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