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000933155 019__ $$a1155872121$$a1157096008$$a1157502201$$a1158334620
000933155 020__ $$a9783030415563$$q(electronic book)
000933155 020__ $$a3030415562$$q(electronic book)
000933155 020__ $$z3030415554
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000933155 0248_ $$a10.1007/978-3-030-41
000933155 035__ $$aSP(OCoLC)on1156611654
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000933155 049__ $$aISEA
000933155 050_4 $$aQA274.23$$b.F75 2020
000933155 08204 $$a519.2$$223
000933155 1001_ $$aFriz, Peter K.,$$d1974-$$eauthor.
000933155 24512 $$aA course on rough paths :$$bwith an introduction to regularity structures /$$cPeter K. Friz, Martin Hairer.
000933155 250__ $$aSecond edition.
000933155 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2020]
000933155 300__ $$a1 online resource.
000933155 336__ $$atext$$btxt$$2rdacontent
000933155 337__ $$acomputer$$bc$$2rdamedia
000933155 338__ $$aonline resource$$bcr$$2rdacarrier
000933155 4901_ $$aUniversitext
000933155 504__ $$aIncludes bibliographical references and index.
000933155 5050_ $$a1 Introduction -- 2 The space of rough paths -- 3 Brownian motion as a rough path -- 4 Integration against rough paths -- 5 Stochastic integration and Itôs formula -- 6 Doob-Meyer type decomposition for rough paths -- 7 Operations on controlled rough paths -- 8 Solutions to rough differential equations -- 9 Stochastic differential equations -- 10 Gaussian rough paths -- 11 Cameron-Martin regularity and applications -- 12 Stochastic partial differential equations -- 13 Introduction to regularity structures -- 14 Operations on modelled distributions -- 15 Application to the KPZ equation -- References -- Index.
000933155 506__ $$aAccess limited to authorized users.
000933155 520__ $$aWith many updates and additional exercises, the second edition of this book continues to provide readers with a gentle introduction to rough path analysis and regularity structures, theories that have yielded many new insights into the analysis of stochastic differential equations, and, most recently, stochastic partial differential equations. Rough path analysis provides the means for constructing a pathwise solution theory for stochastic differential equations which, in many respects, behaves like the theory of deterministic differential equations and permits a clean break between analytical and probabilistic arguments. Together with the theory of regularity structures, it forms a robust toolbox, allowing the recovery of many classical results without having to rely on specific probabilistic properties such as adaptedness or the martingale property. Essentially self-contained, this textbook puts the emphasis on ideas and short arguments, rather than aiming for the strongest possible statements. A typical reader will have been exposed to upper undergraduate analysis and probability courses, with little more than Itô-integration against Brownian motion required for most of the text.
000933155 588__ $$aDescription based on online resource; title from digital title page (viewed on June 15, 2020).
000933155 650_0 $$aStochastic differential equations.
000933155 7001_ $$aHairer, Martin,$$eauthor.
000933155 77608 $$iPrint version: $$z3030415554$$z9783030415556$$w(OCoLC)1137822234
000933155 830_0 $$aUniversitext.
000933155 852__ $$bebk
000933155 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-41556-3$$zOnline Access$$91397441.1
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000933155 980__ $$aEBOOK
000933155 980__ $$aBIB
000933155 982__ $$aEbook
000933155 983__ $$aOnline
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