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999 _c478573
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001 18276543
003 NUST
005 20180605044054.0
008 140822t20142014nyua b 001 0 eng d
010 _a 2014949241
015 _aGBB507717
_2bnb
016 7 _a017003743
_2Uk
020 _a9781493913220
_q(hd. bd.)
020 _a1493913220
_q(hd. bd.)
020 _z9781493913237
_q(eBook)
035 _a(OCoLC)ocn898121925
038 _aSNS Library
040 _aOHX
_beng
_cOHX
_dOCLCO
_dCUD
_dOCLCO
_dOCLCF
_dUKMGB
_dCDX
_dYDXCP
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042 _alccopycat
050 0 0 _aQA274
_b.P385 2014
072 7 _aQA
_2lcco
082 0 4 _a515.4 PAV 2014
_223
100 1 _aPavliotis, Grigorios A.,
_eauthor.
_910953
245 1 0 _aStochastic Processes and Applications :
_bdiffusion processes, the Fokker-Planck and Langevin equations /
_cGrigorios A. Pavliotis.
264 1 _aNew York :
_bSpringer,
_c[2014]
264 4 _c©2014
300 _axiii, 339 pages :
_billustrations (some color) ;Hb.
_c25 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
490 1 _aTexts in applied mathematics,
_x0939-2475 ;
_vvolume 60
500 _aTextbook for graduates.
504 _aIncludes bibliographical references (pages 321-334) and index.
520 _aThis book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.--
_cSource other than Library of Congress.
650 0 _aStochastic processes
_vTextbooks.
_910954
650 0 _aStochastic models
_vTextbooks.
_910955
650 7 _aStochastic models.
_2fast
_0(OCoLC)fst01737780
_910956
650 7 _aStochastic processes.
_2fast
_0(OCoLC)fst01133519
_910957
650 7 _aStochastik.
_2gnd
_0(DE-588)4121729-9
_910958
650 7 _aStatistik.
_2gnd
_0(DE-588)4056995-0
_910959
655 7 _aTextbooks.
_2fast
_0(OCoLC)fst01423863
_910960
776 0 _z9781493913237
776 0 _w(GyWOH)har140494766
830 0 _aTexts in applied mathematics ;
_v60.
_910961
856 4 2 _3Contributor biographical information
_uhttps://www.loc.gov/catdir/enhancements/fy1617/2014949241-b.html
856 4 2 _3Publisher description
_uhttps://www.loc.gov/catdir/enhancements/fy1617/2014949241-d.html
856 4 1 _3Table of contents only
_uhttps://www.loc.gov/catdir/enhancements/fy1617/2014949241-t.html
906 _a7
_bcbc
_ccopycat
_d2
_eepcn
_f20
_gy-gencatlg
942 _2ddc
_cBK