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001			287062
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007			cr nn 008mamaa
008			150903s2012 xxk| o |||| 0|eng d
020			_a9781447122333 _99781447122333
024	7		_a10.1007/9781447122333 _2doi
035			_avtls000339526
039		9	_a201509030839 _bVLOAD _c201404300401 _dVLOAD _y201402060937 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTK5102.9
100	1		_aSheng, Hu. _eautor _9316068
245	1	0	_aFractional Processes and Fractional-Order Signal Processing : _bTechniques and Applications / _cby Hu Sheng, YangQuan Chen, TianShuang Qiu.
264		1	_aLondon : _bSpringer London, _c2012.
300			_axxvI, 295 páginas 162 ilustraciones, 146 ilustraciones en color. _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSignals and Communication Technology, _x1860-4862
500			_aSpringer eBooks
505	0		_aPart I: Overview of Fractional Processes and Fractional-order Signal Processing -- Introduction -- Overview of Fractional Processes and Fractional-order Signal Processing -- Part II: Fractional Processes -- Constant-order Fractional Processes -- Multifractional Processes -- Part III: Fractional-order Signal Processing -- Constant-order Fractional Signal Processing -- Variable-order Fractional Signal Processing -- Distributed-order Fractional Signal Processing -- Part IV: Applications of Fractional-order Signal Processing Techniques -- FARIMA with Stable Innovations Model of Great Salt Lake Elevation -- Analysis of ECN Using Fractional Signal Processing Techniques -- Optimal Fractional-order Damping Strategies -- Heavy-tailed Distribution and Local Long Memory in Molecular Motion -- Multifractional Property Analysis of Human Sleep EEG Signals -- Conclusions -- Appendices: Mittag-Leffler Functions; Application of Numerical Inverse Laplace Transform Algorithms in Fractional-order Signal Processing; Some Useful Webpages; MATLAB® Codes of Impulse–Response Invariant Discretization of Fractional-order Filters.
520			_aFractional processes are widely found in science, technology and engineering systems. In Fractional Processes and Fractional-order Signal Processing, some complex random signals, characterized by the presence of a heavy-tailed distribution or non-negligible dependence between distant observations (local and long memory), are introduced and examined from the ‘fractional’ perspective using simulation, fractional-order modeling and filtering and realization of fractional-order systems. These fractional-order signal processing (FOSP) techniques are based on fractional calculus, the fractional Fourier transform and fractional lower-order moments. Fractional Processes and Fractional-order Signal Processing: • presents fractional processes of fixed, variable and distributed order studied as the output of fractional-order differential systems; • introduces FOSP techniques and the fractional signals and fractional systems point of view; • details real-world-application examples of FOSP techniques to demonstrate their utility; and • provides important background material on Mittag–Leffler functions, the use of numerical inverse Laplace transform algorithms and supporting MATLAB® codes together with a helpful survey of relevant webpages. Readers will be able to use the techniques presented to re-examine their signals and signal-processing methods. This text offers an extended toolbox for complex signals from diverse fields in science and engineering. It will give academic researchers and practitioners a novel insight into the complex random signals characterized by fractional properties, and some powerful tools to analyze those signals.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aChen, YangQuan. _eautor _9316069
700	1		_aQiu, TianShuang. _eautor _9316070
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781447122326
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4471-2233-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c287062 _d287062