000			02646nam a22003858i 4500
001			CR9781139086561
003			UkCbUP
005			20200124160236.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			110512s1989||||enk o ||1 0|eng|d
020			_a9781139086561 (ebook)
020			_z9780521345354 (hardback)
020			_z9780521089784 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA273.5 _b.A45 1989
082	0	0	_a519.2 _220
100	1		_aAmbartzumian, R. V., _eauthor.
245	1	0	_aFactorization calculus and geometric probability / _cR.V. Ambartzumian.
246	3		_aFactorization Calculus & Geometric Probability
264		1	_aCambridge : _bCambridge University Press, _c1989.
300			_a1 online resource (xi, 286 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aEncyclopedia of mathematics and its applications ; _vvolume 33
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aThis unique book develops the classical subjects of geometric probability and integral geometry, and the more modern one of stochastic geometry, in rather a novel way to provide a unifying framework in which they can be studied. The author focuses on factorisation properties of measures and probabilities implied by the assumption of their invariance with respect to a group, in order to investigate non-trivial factors. The study of these properties is the central theme of the book. Basic facts about integral geometry and random point process theory are developed in a simple geometric way, so that the whole approach is suitable for a non-specialist audience. Even in the later chapters, where the factorisation principles are applied to geometrical processes, the prerequisites are only standard courses on probability and analysis. The main ideas presented here have application to such areas as stereology and tomography, geometrical statistics, pattern and texture analysis. This book will be well suited as a starting point for individuals working in those areas to learn about the mathematical framework. It will also prove valuable as an introduction to geometric probability theory and integral geometry based on modern ideas.
650		0	_aStochastic geometry.
650		0	_aGeometric probabilities.
650		0	_aFactorization (Mathematics)
776	0	8	_iPrint version: _z9780521345354
830		0	_aEncyclopedia of mathematics and its applications ; _vv. 33.
856	4	0	_uhttps://doi.org/10.1017/CBO9781139086561
999			_c518125 _d518123