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Add to basketXIV, 145 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Understanding Complex Systems. Sprache: Englisch.
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Seller: Revaluation Books, Exeter, United Kingdom
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Published by Münchner Verlagsgruppe GmbH, 2017
ISBN 10: 3868816666 ISBN 13: 9783868816662
Language: German
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Add to basketCondition: New. Autor/Autorin: Petr LudwigPetr Ludwig ist Wissenschaftspopularisator und Berater von Fortune-500-Unternehmen in Europa. Der studierte Jurist und IT-Spezialist erklaert entscheidende und schwierige Zusammenhaenge einfach und allgemein verstaendlich. Er.
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Add to basketGebunden. Condition: New. KlappentextThe celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new contex.
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Published by Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319866451 ISBN 13: 9783319866451
Language: English
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer's toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory-data processing inequality-states that deterministic processing always involves information loss. These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.
Published by Springer International Publishing, 2017
ISBN 10: 3319595326 ISBN 13: 9783319595320
Language: English
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer's toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory-data processing inequality-states that deterministic processing always involves information loss. These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.
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Published by Springer International Publishing, Springer Nature Switzerland Aug 2018, 2018
ISBN 10: 3319866451 ISBN 13: 9783319866451
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch.
Published by Springer International Publishing, Springer Nature Switzerland Jul 2017, 2017
ISBN 10: 3319595326 ISBN 13: 9783319595320
Language: English
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Add to basketBuch. Condition: Neu. Neuware -statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch.
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Seller: Revaluation Books, Exeter, United Kingdom
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Published by LIGHTNING SOURCE UK LTD, 2021
ISBN 10: 3036508023 ISBN 13: 9783036508023
Language: English
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Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by LIGHTNING SOURCE UK LTD, 2021
ISBN 10: 3036508023 ISBN 13: 9783036508023
Language: English
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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Add to basketHRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: ¿ provide novel insights into the functional properties of the IB; ¿ discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and ¿ offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information-theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence.
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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