000 03329nam a22005295i 4500
001 978-1-4419-9476-9
003 DE-He213
005 20140220083729.0
007 cr nn 008mamaa
008 110406s2011 xxu| s |||| 0|eng d
020 _a9781441994769
_9978-1-4419-9476-9
024 7 _a10.1007/978-1-4419-9476-9
_2doi
050 4 _aQA372
072 7 _aPBKJ
_2bicssc
072 7 _aMAT007000
_2bisacsh
082 0 4 _a515.352
_223
100 1 _aBezandry, Paul H.
_eauthor.
245 1 0 _aAlmost Periodic Stochastic Processes
_h[electronic resource] /
_cby Paul H. Bezandry, Toka Diagana.
264 1 _aNew York, NY :
_bSpringer New York,
_c2011.
300 _aXV, 235p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
520 _aAlmost Periodic Stochastic Processes is among the few published books that is entirely devoted to almost periodic stochastic processes and their applications.  The topics treated range from existence, uniqueness, boundedness, and stability of solutions, to stochastic difference and differential equations. Motivated by the studies of the natural fluctuations in nature, this work aims to lay the foundations for a theory on almost periodic stochastic processes and their applications. This book is divided in to eight chapters and offers useful bibliographical notes at the end of each chapter. Highlights of this monograph include the introduction of the concept of p-th mean almost periodicity for stochastic processes and applications to various equations. The book offers some original results on the boundedness, stability, and existence of p-th mean almost periodic solutions to (non)autonomous first and/or second order stochastic differential equations, stochastic partial differential equations, stochastic functional differential equations with delay, and stochastic difference equations.  Various illustrative examples are also discussed throughout the book. The results provided in the book will be of particular use to those conducting research in the field of stochastic processing including engineers, economists, and statisticians with backgrounds in functional analysis and stochastic analysis.   Advanced graduate students with backgrounds in real analysis, measure theory, and basic probability, may also find the material in this book quite useful and engaging.
650 0 _aMathematics.
650 0 _aFunctional analysis.
650 0 _aIntegral equations.
650 0 _aOperator theory.
650 0 _aDifferential Equations.
650 0 _aDifferential equations, partial.
650 0 _aDistribution (Probability theory).
650 1 4 _aMathematics.
650 2 4 _aOrdinary Differential Equations.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aPartial Differential Equations.
650 2 4 _aFunctional Analysis.
650 2 4 _aOperator Theory.
650 2 4 _aIntegral Equations.
700 1 _aDiagana, Toka.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441994752
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-9476-9
912 _aZDB-2-SMA
999 _c106059
_d106059