Isbn: 9783032165886 - vertex-frequency analysis of graph signals (7 risultati)

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    • Lingua: Inglese

      Editore: Springer, 2026

      3032165881 / 9783032165886

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      Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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      EUR 300,79

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    • Lingua: Inglese

      Editore: Springer, 2026

      3032165881 / 9783032165886

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      EUR 299,66

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      Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces new methods to analyze vertex-varying graph signals. In many real-world scenarios, the data-sensing domain is not a regular grid, but a more complex network that consists of sensing points (vertices) and edges (relating the sensing points). Furthermore, sensing geometry or signal properties define the relation among sensed signal points. Even for the data sensed in the well-defined time or space domain, the introduction of new relationships among the sensing points may produce new insights in the analysis and result in more advanced data processing techniques. The data domain, in these cases and discussed in this book, is defined by a graph. Graphs exploit the fundamental relations among the data points.Although signal processing techniques for the analysis of time-varying signals are well established, the corresponding graph signal processing equivalent approaches are still in their infancy. This book presents novel approaches to analyze vertex-varying graph signals. The vertex-frequency analysis methods use the Laplacian or adjacency matrix to establish connections between vertex and spectral (frequency) domain in order to analyze local signal behavior where edge connections are used for graph signal localization. The book applies combined concepts from time-frequency and wavelet analyses of classical signal processing to the analysis of graph signals.This second edition has been revised and updated and has now been expanded to include new chapters on cutting-edge topics relevant to the analysis of graph signals such as machine learning.Covering analytical tools for vertex-varying applications, this book is of interest to researchers and practitioners in engineering, science, neuroscience, genome processing, just to name a few. It is also a valuable resource for postgraduate students and researchers looking to expand their knowledge of the vertex-frequency analysis theory and its applications.

    • Lingua: Inglese

      Editore: Springer Verlag GmbH, 2026

      3032165881 / 9783032165886

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      Da: moluna, Greven, Germaniamoluna

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      EUR 180,07

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

    • Lingua: Inglese

      Editore: Springer Nature Switzerland AG Mai 2026, 2026

      3032165881 / 9783032165886

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      EUR 213,99

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      Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces new methods to analyze vertex-varying graph signals. In many real-world scenarios, the data-sensing domain is not a regular grid, but a more complex network that consists of sensing points (vertices) and edges (relating the sensing points). Furthermore, sensing geometry or signal properties define the relation among sensed signal points. Even for the data sensed in the well-defined time or space domain, the introduction of new relationships among the sensing points may produce new insights in the analysis and result in more advanced data processing techniques. The data domain, in these cases and discussed in this book, is defined by a graph. Graphs exploit the fundamental relations among the data points.Although signal processing techniques for the analysis of time-varying signals are well established, the corresponding graph signal processing equivalent approaches are still in their infancy. This book presents novel approaches to analyze vertex-varying graph signals. The vertex-frequency analysis methods use the Laplacian or adjacency matrix to establish connections between vertex and spectral (frequency) domain in order to analyze local signal behavior where edge connections are used for graph signal localization. The book applies combined concepts from time-frequency and wavelet analyses of classical signal processing to the analysis of graph signals.This second edition has been revised and updated and has now been expanded to include new chapters on cutting-edge topics relevant to the analysis of graph signals such as machine learning.Covering analytical tools for vertex-varying applications, this book is of interest to researchers and practitioners in engineering, science, neuroscience, genome processing, just to name a few. It is also a valuable resource for postgraduate students and researchers looking to expand their knowledge of the vertex-frequency analysis theory and its applications. 555 pp. Englisch.

    • Lingua: Inglese

      Editore: Springer Jun 2026, 2026

      3032165881 / 9783032165886

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      EUR 213,99

      EUR 60,00 spedizione 
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      Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces new methods to analyze vertex-varying graph signals. In many real-world scenarios, the data-sensing domain is not a regular grid, but a more complex network that consists of sensing points (vertices) and edges (relating the sensing points). Furthermore, sensing geometry or signal properties define the relation among sensed signal points. Even for the data sensed in the well-defined time or space domain, the introduction of new relationships among the sensing points may produce new insights in the analysis and result in more advanced data processing techniques. The data domain, in these cases and discussed in this book, is defined by a graph. Graphs exploit the fundamental relations among the data points. Although signal processing techniques for the analysis of time-varying signals are well established, the corresponding graph signal processing equivalent approaches are still in their infancy. This book presents novel approaches to analyze vertex-varying graph signals. The vertex-frequency analysis methods use the Laplacian or adjacency matrix to establish connections between vertex and spectral (frequency) domain in order to analyze local signal behavior where edge connections are used for graph signal localization. The book applies combined concepts from time-frequency and wavelet analyses of classical signal processing to the analysis of graph signals.This second edition has been revised and updated and has now been expanded to include new chapters on cutting-edge topics relevant to the analysis of graph signals such as machine learning.Covering analytical tools for vertex-varying applications, this book is of interest to researchers and practitioners in engineering, science, neuroscience, genome processing, just to name a few. It is also a valuable resource for postgraduate students and researchers looking to expand their knowledge of the vertex-frequency analysis theory and its applications.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 572 pp. Englisch.

    • Lingua: Inglese

      Editore: Springer, 2026

      3032165881 / 9783032165886

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      Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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      EUR 313,83

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    • Lingua: Inglese

      Editore: Springer, 2026

      3032165881 / 9783032165886

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      Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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      EUR 318,55

      EUR 9,95 spedizione 
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      Condizione: New. PRINT ON DEMAND.