000			03391nam a22004215i 4500
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007			cr nn 008mamaa
008			170703s2018 gw | s |||| 0|eng d
020			_a9783319595337
024	7		_a10.1007/978-3-319-59533-7 _2doi
040			_bspa _dES-MaUEC
050		4	_aTK5102.9 _b2018 EB
100	1		_aGeiger, Bernhard C. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/74644867/
245	1	0	_aInformation Loss in Deterministic Signal Processing Systems _cby Bernhard C. Geiger, Gernot Kubin.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XIII, 145 páginas 16 ilustraciones, 9 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aUnderstanding Complex Systems, _x1860-0832
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction -- Part I: Random Variables -- Piecewise Bijective Functions and Continuous Inputs -- General Input Distributions -- Dimensionality-Reducing Functions -- Relevant Information Loss -- II. Part II: Stationary Stochastic Processes -- Discrete-Valued Processes -- Piecewise Bijective Functions and Continuous Inputs -- Dimensionality-Reducing Functions -- Relevant Information Loss Rate -- Conclusion and Outlook.
520	3		_aThis book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer's toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory-data processing inequality-states that deterministic processing always involves information loss.  These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.
988			_aEBSPRINGER_2018
650		7	_9150609 _aProceso digital de señales _2embne
700	1		_aKubin, Gernot. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iEdición impresa: _z9783319595320
776	0	8	_iEdición impresa: _z9783319595344
776	0	8	_iEdición impresa: _z9783319866451
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-59533-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2019 _dz _zSI _eIG