000			03207nam a22004815i 4500
001			978-3-540-68829-7
003			DE-He213
005			20160302162932.0
007			cr nn 008mamaa
008			100301s2007 gw | s |||| 0|eng d
020			_a9783540688297 _9978-3-540-68829-7
024	7		_a10.1007/978-3-540-68829-7 _2doi
050		4	_aQA273.A1-274.9
050		4	_aQA274-274.9
072		7	_aPBT _2bicssc
072		7	_aPBWL _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.2 _223
100	1		_aKoralov, Leonid. _eauthor.
245	1	0	_aTheory of Probability and Random Processes _h[electronic resource] / _cby Leonid Koralov, Yakov G. Sinai.
250			_aSecond.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2007.
300			_aXI, 358 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUniversitext, _x0172-5939
505	0		_aProbability Theory -- Random Variables and Their Distributions -- Sequences of Independent Trials -- Lebesgue Integral and Mathematical Expectation -- Conditional Probabilities and Independence -- Markov Chains with a Finite Number of States -- Random Walks on the Lattice ?d -- Laws of Large Numbers -- Weak Convergence of Measures -- Characteristic Functions -- Limit Theorems -- Several Interesting Problems -- Random Processes -- Basic Concepts -- Conditional Expectations and Martingales -- Markov Processes with a Finite State Space -- Wide-Sense Stationary Random Processes -- Strictly Stationary Random Processes -- Generalized Random Processes -- Brownian Motion -- Markov Processes and Markov Families -- Stochastic Integral and the Ito Formula -- Stochastic Differential Equations -- Gibbs Random Fields.
520			_aA one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of the content of this book It is structured in two parts: the first part providing a detailed discussion of Lebesgue integration, Markov chains, random walks, laws of large numbers, limit theorems, and their relation to Renormalization Group theory. The second part includes the theory of stationary random processes, martingales, generalized random processes, Brownian motion, stochastic integrals, and stochastic differential equations. One section is devoted to the theory of Gibbs random fields. This material is essential to many undergraduate and graduate courses. The book can also serve as a reference for scientists using modern probability theory in their research.
650		0	_aMathematics.
650		0	_aProbabilities.
650	1	4	_aMathematics.
650	2	4	_aProbability Theory and Stochastic Processes.
700	1		_aSinai, Yakov G. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540254843
830		0	_aUniversitext, _x0172-5939
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-540-68829-7
912			_aZDB-2-SMA
999			_c179092 _d179092