000			02092nam a22003738i 4500
001			CR9780511613586
003			UkCbUP
005			20200124160221.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			090914s2002||||enk o ||1 0|eng|d
020			_a9780511613586 (ebook)
020			_z9780521813570 (hardback)
020			_z9780521890014 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA274.7 _b.H34 2002
082	0	0	_a511.8 _221
100	1		_aHäggström, Olle, _eauthor.
245	1	0	_aFinite Markov chains and algorithmic applications / _cOlle Häggström.
246	3		_aFinite Markov Chains & Algorithmic Applications
264		1	_aCambridge : _bCambridge University Press, _c2002.
300			_a1 online resource (ix, 114 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aLondon Mathematical Society student texts ; _v52
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aBased on a lecture course given at Chalmers University of Technology, this 2002 book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range of randomized algorithms with important applications in optimization and other problems in computing. Amongst the algorithms covered are the Markov chain Monte Carlo method, simulated annealing, and the recent Propp-Wilson algorithm. This book will appeal not only to mathematicians, but also to students of statistics and computer science. The subject matter is introduced in a clear and concise fashion and the numerous exercises included will help students to deepen their understanding.
650		0	_aMarkov processes.
650		0	_aAlgorithms.
776	0	8	_iPrint version: _z9780521813570
830		0	_aLondon Mathematical Society student texts ; _v52.
856	4	0	_uhttps://doi.org/10.1017/CBO9780511613586
999			_c516706 _d516704