000			02124nam a22003377a 4500
003			OSt
005			20250226095158.0
008			250224b |||||||| |||| 00| 0 hin d
020			_a9783319740171
040			_aNISER LIBRARY _beng _cNISER LIBRARY
082			_a519.216 _bCOL-D
100			_aCollet, Jean-François
245			_aDiscrete stochastic processes and applications
260			_aCham, Switzerland : _bSpringer, _c2018.
300			_axvii, 220 pages : _billustrations (3 b/w illustrations)
490			_aUniversitext, _x0172-5939
504			_aIncludes bibliographical references and index
520			_aThis unique text for beginning graduate students gives a self-contained introduction to the mathematical properties of stochastics and presents their applications to Markov processes, coding theory, population dynamics, and search engine design. The book is ideal for a newly designed course in an introduction to probability and information theory. Prerequisites include working knowledge of linear algebra, calculus, and probability theory. The first part of the text focuses on the rigorous theory of Markov processes on countable spaces (Markov chains) and provides the basis to developing solid probabilistic intuition without the need for a course in measure theory. The approach taken is gradual beginning with the case of discrete time and moving on to that of continuous time. The second part of this text is more applied; its core introduces various uses of convexity in probability and presents a nice treatment of entropy.
650			_aStochastic processes
650			_aMarkov processes
650			_aBrownian motion
650			_aPerron-Frobenius theorem
650			_aPoisson process
650			_aInformation theory
650			_aProbability information theory
650			_aCoding theory
650			_aPopulation dynamics
856			_3Table of content _uhttps://link.springer.com/content/pdf/bfm:978-3-319-74018-8/1
856			_3Reviews _uhttps://www.goodreads.com/book/show/43385000-discrete-stochastic-processes-and-applications#CommunityReviews
942			_2udc _cBK
999			_c35756 _d35756