000			02909nam a22003855i 4500
001			394183
003			ES-MaUEC
005			20230102123102.0
007			cr nn 008mamaa
008			221015s2022 sz | s |||| 0|eng d
020			_a9783031167805
024	7		_a10.1007/978-3-031-16780-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aUrenda, Julio C _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aAlgebraic Approach to Data Processing _bTechniques and Applications _cby Julio C Urenda, Vladik Kreinovich
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIII, 250 páginas) _b8 ilustraciones, 4 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Big Data _x2197-6511 _v115
505	0		_aIntroduction -- What Are the Most Natural and the Most Frequent Transformations -- Which Functions and Which Families of Functions Are Invariant -- What Is the General Relation Between Invariance And Optimality -- General Application: Dynamical Systems -- First Application to Physics: Why Liquids? -- Second Application to Physics: Warping of Our Galaxy.
520			_aThe book explores a new general approach to selecting-and designing-data processing techniques. Symmetry and invariance ideas behind this algebraic approach have been successful in physics, where many new theories are formulated in symmetry terms. The book explains this approach and expands it to new application areas ranging from engineering, medicine, education to social sciences. In many cases, this approach leads to optimal techniques and optimal solutions. That the same data processing techniques help us better analyze wooden structures, lung dysfunctions, and deep learning algorithms is a good indication that these techniques can be used in many other applications as well. The book is recommended to researchers and practitioners who need to select a data processing technique-or who want to design a new technique when the existing techniques do not work. It is also recommended to students who want to learn the state-of-the-art data processing. .
700	1		_aKreinovich, Vladik _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783031167799
776	0	8	_iPrinted edition: _z9783031167812
776	0	8	_iPrinted edition: _z9783031167829
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-16780-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394183 _d394183