000 | 04007nam a22006255i 4500 | ||
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001 | 978-3-319-75049-1 | ||
003 | DE-He213 | ||
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007 | cr nn 008mamaa | ||
008 | 180224s2018 sz | s |||| 0|eng d | ||
020 |
_a9783319750491 _9978-3-319-75049-1 |
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024 | 7 |
_a10.1007/978-3-319-75049-1 _2doi |
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072 | 7 |
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_aUYQ _2thema |
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_a006.3 _223 |
100 | 1 |
_aBuscema, Paolo Massimo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956507 |
|
245 | 1 | 0 |
_aArtificial Adaptive Systems Using Auto Contractive Maps _h[electronic resource] : _bTheory, Applications and Extensions / _cby Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman, Masoud Asadi-Zeydabadi. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
|
300 |
_aVII, 179 p. 97 illus., 74 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 |
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490 | 1 |
_aStudies in Systems, Decision and Control, _x2198-4190 ; _v131 |
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505 | 0 | _aAn Introduction -- Artificial Neural Networks -- Auto-Contractive Maps -- Visualization of Auto-CM Output -- Dataset Transformations and Auto-CM -- Comparison of Auto-CM to Various Other Data Understanding Approaches. | |
520 | _aThis book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory. | ||
650 | 0 |
_aComputational intelligence. _97716 |
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650 | 0 |
_aData mining. _93907 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aMathematical logic. _92258 |
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650 | 1 | 4 |
_aComputational Intelligence. _97716 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _956508 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aMathematical Logic and Foundations. _934712 |
700 | 1 |
_aMassini, Giulia. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956509 |
|
700 | 1 |
_aBreda, Marco. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956510 |
|
700 | 1 |
_aLodwick, Weldon A. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956511 |
|
700 | 1 |
_aNewman, Francis. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956512 |
|
700 | 1 |
_aAsadi-Zeydabadi, Masoud. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _956513 |
|
710 | 2 |
_aSpringerLink (Online service) _956514 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319750484 |
776 | 0 | 8 |
_iPrinted edition: _z9783319750507 |
776 | 0 | 8 |
_iPrinted edition: _z9783030091354 |
830 | 0 |
_aStudies in Systems, Decision and Control, _x2198-4190 ; _v131 _956515 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-75049-1 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
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