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008			200523s2020 gw a o |||| 0|eng d
020			_a9783030453596
024	7		_a10.1007/978-3-030-45359-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5102.9 _b2020 EB
100	1		_aNigmatullin, Raoul R _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/317159402 _9675822
245	1	0	_aNew Digital Signal Processing Methods : _bApplications to Measurement and Diagnostics / _cRaoul R Nigmatullin, Paolo Lino, Guido Maione
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2020
300			_a1 recurso en línea (XX, 443 páginas) _b228 ilustraciones, 108 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aEngineering (Springer-11647)
505	0		_aIn what cases the non-linear fitting problem is reduced to the well-known linear least square method? The Eigen-Coordinates method. -- A nontrivial example of the application of the ECs method: Description of the blow-like signals. -- The statistics of the fractional moments and its application for quantitative "reading" of real data. -- The quantitative "universal" label (QUL) and the universal distribution function for the relative fluctuations (UDFRF). -- Description of the partly correlated random sequences: Replacement of the random sequences by the generalized Prony spectrum. -- The general theory of reproducible and quasi-reproducible experiments. -- Non-orthogonal Amplitude Frequency Analysis of the Smoothed Signals (NAFASS) and its application for the description of multi-frequency signals. -- NIMRAD in action: Application.
520	3		_aThis book is intended as a manual on modern advanced statistical methods for signal processing. The objectives of signal processing are the analysis, synthesis, and modification of signals measured from different natural phenomena, including engineering applications as well. Often the measured signals are affected by noise, distortion and incompleteness, and this makes it difficult to extract significant signal information. The main topic of the book is the extraction of significant information from measured data, with the aim of reducing the data size while keeping the basic information/knowledge about the peculiarities and properties of the analyzed system; to this aim, advanced and recently developed methods in signal analysis and treatment are introduced and described in depth. More in details, the book covers the following new advanced topics (and the corresponding algorithms), including detailed descriptions and discussions: the Eigen-Coordinates (ECs) method, The statistics of the fractional moments, The quantitative "universal" label (QUL) and the universal distribution function for the relative fluctuations (UDFRF), the generalized Prony spectrum, the Non-orthogonal Amplitude Frequency Analysis of the Smoothed Signals (NAFASS), the discrete geometrical invariants (DGI) serving as the common platform for quantitative comparison of different random functions. Although advanced topics are discussed in signal analysis, each subject is introduced gradually, with the use of only the necessary mathematics, and avoiding unnecessary abstractions. Each chapter presents testing and verification examples on real data for each proposed method. In comparison with other books, here it is adopted a more practical approach with numerous real case studies.
988			_aSpringer_Engineering_23062020
650		7	_aProceso digital de señales _2embne _9150609
700	1		_aLino, Paolo _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9675823
700	1		_aMaione, Guido _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9675824
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729
776	0	8	_iPrinted edition: _z9783030453589
776	0	8	_iPrinted edition: _z9783030453602
776	0	8	_iPrinted edition: _z9783030453619
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-45359-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b09/2020 _dz _eo _zSI