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999			_c387146 _d387146
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008			220601s2006 sz | s |||| 0|eng d
020			_a9783031016158
024	7		_a10.1007/978-3-031-01615-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA273 _b2006 EB
100	1		_aEnderle, John D. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686113 _q(John Denis)
245	1	0	_aAdvanced Probability Theory for Biomedical Engineers _cby John Enderle, David Farden, Daniel Krause
250			_a1st edition 2006
264		1	_aCham _bSpringer International Publishing _c2006
300			_a1 recurso en línea (VIII, 100 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Biomedical Engineering _x1930-0336
520			_aThis is the third in a series of short books on probability theory and random processes for biomedical engineers. This book focuses on standard probability distributions commonly encountered in biomedical engineering. The exponential, Poisson and Gaussian distributions are introduced, as well as important approximations to the Bernoulli PMF and Gaussian CDF. Many important properties of jointly Gaussian random variables are presented. The primary subjects of the final chapter are methods for determining the probability distribution of a function of a random variable. We first evaluate the probability distribution of a function of one random variable using the CDF and then the PDF. Next, the probability distribution for a single random variable is determined from a function of two random variables using the CDF. Then, the joint probability distribution is found from a function of two random variables using the joint PDF and the CDF. The aim of all three books is as an introduction to probability theory. The audience includes students, engineers and researchers presenting applications of this theory to a wide variety of problems-as well as pursuing these topics at a more advanced level. The theory material is presented in a logical manner-developing special mathematical skills as needed. The mathematical background required of the reader is basic knowledge of differential calculus. Pertinent biomedical engineering examples are throughout the text. Drill problems, straightforward exercises designed to reinforce concepts and develop problem solution skills, follow most sections.
988			_aSynthesis Collection of Technology_2006
650		7	_2embne _9405075 _aProbabilidades
650		7	_2embne _9475879 _aVariables aleatorias
650		7	_2embne _9143820 _aIngeniería biomédica
700	1		_aFarden, David Charles _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686679
700	1		_aKrause, Daniel J. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686680
776	0	8	_iPrinted edition: _z9783031004872
776	0	8	_iPrinted edition: _z9783031027437
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01615-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI