Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 502 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Zustand: New. 2010. Paperback. . . . . . Books ship from the US and Ireland.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 100 pages. 9.50x6.50x0.25 inches. In Stock.
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 502 pages. 10.00x8.00x1.40 inches. In Stock.
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 502 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Zustand: New. 2009. Hardcover. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Berlin, Springer Berlin / Heidelberg, 2009
ISBN 10: 3540880763 ISBN 13: 9783540880769
Anbieter: Antiquariat Bookfarm, Löbnitz, Deutschland
Hardcover. 108 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. 9783540880769 Sprache: Englisch Gewicht in Gramm: 550.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2009, 2009
ISBN 10: 3540880763 ISBN 13: 9783540880769
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. Neuware -In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB.The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 116 pp. Englisch.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2010
ISBN 10: 3642099858 ISBN 13: 9783642099854
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, 2009
ISBN 10: 3540880763 ISBN 13: 9783540880769
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.