000			02100nam a2200325 i 4500
001			CR9781108552349
003			UkCbUP
005			20240730160733.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			170919s2022||||enk o ||1 0|eng|d
020			_a9781108552349 (ebook)
020			_z9781108428132 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aTK5102.9 _b.O77 2022
082	0	0	_a621.382/2 _223
100	1		_aOrtega, Antonio, _d1965- _eauthor. _974275
245	1	0	_aIntroduction to graph signal processing / _cAntonio Ortega, University of Southern California.
264		1	_aCambridge : _bCambridge University Press, _c2022.
300			_a1 online resource (xvii, 301 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 07 Apr 2022).
520			_aAn intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.
650		0	_aSignal processing. _94052
776	0	8	_iPrint version: _z9781108428132
856	4	0	_uhttps://doi.org/10.1017/9781108552349
942			_cEBK
999			_c84079 _d84079