02452nmm a2200373 u 4500001001200000003002700012005001700039007002400056008004100080020001800121100002200139245014200161250001700303260005600320300005900376505012500435653002400560653002800584653001900612653003200631653003700663653003600700653004800736653002700784653001800811700002800829710003400857041001900891989003600910490003400946856007200980082001201052520101401064EB001345458EBX0100000000000000089964800000000000000.0cr|||||||||||||||||||||170203 ||| eng a97833194924761 aCaraballo, Tomás00aApplied Nonautonomous and Random Dynamical SystemshElektronische RessourcebApplied Dynamical Systemscby Tomás Caraballo, Xiaoying Han a1st ed. 2016 aChambSpringer International Publishingc2016, 2016 aX, 108 p. 7 illus., 4 illus. in colorbonline resource0 a1 Introduction -- 2 Autonomous dynamical systems. - 3 Nonautonomous dynamical systems -- 4 Random dynamical - References aApplied mathematics aEngineering mathematics aBiomathematics aApplications of Mathematics aGenetics and Population Dynamics aOrdinary Differential Equations aProbability Theory and Stochastic Processes aDifferential equations aProbabilities1 aHan, Xiaoyinge[author]2 aSpringerLink (Online service)07aeng2ISO 639-2 bSpringeraSpringer eBooks 2005-0 aSpringerBriefs in Mathematics uhttps://doi.org/10.1007/978-3-319-49247-6?nosfx=yxVerlag3Volltext0 a515.352 aThis book offers an introduction to the theory of non-autonomous and stochastic dynamical systems, with a focus on the importance of the theory in the Applied Sciences. It starts by discussing the basic concepts from the theory of autonomous dynamical systems, which are easier to understand and can be used as the motivation for the non-autonomous and stochastic situations. The book subsequently establishes a framework for non-autonomous dynamical systems, and in particular describes the various approaches currently available for analysing the long-term behaviour of non-autonomous problems. Here, the major focus is on the novel theory of pullback attractors, which is still under development. In turn, the third part represents the main body of the book, introducing the theory of random dynamical systems and random attractors and revealing how it may be a suitable candidate for handling realistic models with stochasticity. A discussion of future research directions serves to round out the coverage