000 | 03315nam a22005535i 4500 | ||
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001 | 978-3-031-16780-5 | ||
003 | DE-He213 | ||
005 | 20240423125100.0 | ||
007 | cr nn 008mamaa | ||
008 | 221015s2022 sz | s |||| 0|eng d | ||
020 |
_a9783031167805 _9978-3-031-16780-5 |
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024 | 7 |
_a10.1007/978-3-031-16780-5 _2doi |
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050 | 4 | _aTA345-345.5 | |
072 | 7 |
_aUN _2bicssc |
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072 | 7 |
_aCOM018000 _2bisacsh |
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072 | 7 |
_aUN _2thema |
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082 | 0 | 4 |
_a620.00285 _223 |
100 | 1 |
_aUrenda, Julio C. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
245 | 1 | 0 |
_aAlgebraic Approach to Data Processing _h[electronic resource] : _bTechniques and Applications / _cby Julio C. Urenda, Vladik Kreinovich. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
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300 |
_aXIII, 250 p. 8 illus., 4 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aStudies in Big Data, _x2197-6511 ; _v115 |
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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. . | ||
650 | 0 |
_aEngineering _xData processing. |
|
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aBig data. | |
650 | 1 | 4 | _aData Engineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aBig Data. |
700 | 1 |
_aKreinovich, Vladik. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031167799 |
776 | 0 | 8 |
_iPrinted edition: _z9783031167812 |
776 | 0 | 8 |
_iPrinted edition: _z9783031167829 |
830 | 0 |
_aStudies in Big Data, _x2197-6511 ; _v115 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-16780-5 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c174023 _d174023 |