The Resource Vertex-Frequency Analysis of Graph Signals, edited by Ljubiša Stanković, Ervin Sejdić, (electronic resource)

Vertex-Frequency Analysis of Graph Signals, edited by Ljubiša Stanković, Ervin Sejdić, (electronic resource)

Label
Vertex-Frequency Analysis of Graph Signals
Title
Vertex-Frequency Analysis of Graph Signals
Statement of responsibility
edited by Ljubiša Stanković, Ervin Sejdić
Contributor
Editor
Editor
Subject
Language
eng
Summary
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. Processing of signals whose sensing domains are defined by graphs resulted in graph data processing as an emerging field in signal processing. 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. 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. The book consists of 15 chapters contributed by 41 leading researches in the field
Member of
Dewey number
511.5
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt
  • 6ocM3jN7dZI
  • _tTjaO8IOyY
LC call number
  • TK5102.9
  • TA1637-1638
  • TK7882.S65
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Stanković, Ljubiša.
  • Sejdić, Ervin.
Series statement
Signals and Communication Technology,
http://library.link/vocab/subjectName
  • Neurosciences
  • Signal, Image and Speech Processing
  • Graph Theory
  • Applications of Graph Theory and Complex Networks
  • Neurosciences
Label
Vertex-Frequency Analysis of Graph Signals, edited by Ljubiša Stanković, Ervin Sejdić, (electronic resource)
Instantiates
Publication
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Introduction to Graph Signal Processing -- Oversampled Graph Laplacian Matrix for Graph Filter Banks -- Toward an Uncertainty Principle for Weighted Graphs -- Graph Theoretic Uncertainty and Feasibility -- Signal-Adapted Tight Frames on Graphs -- Local Spectral Analysis of the Cerebral Cortex: New Gyrification Indices -- Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets
Dimensions
unknown
Edition
1st ed. 2019.
Extent
1 online resource (516 pages)
Form of item
online
Isbn
9783030035747
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-030-03574-7
Sound
unknown sound
Specific material designation
remote
System control number
  • (CKB)4100000007181329
  • (MiAaPQ)EBC5608255
  • (DE-He213)978-3-030-03574-7
  • (EXLCZ)994100000007181329
Label
Vertex-Frequency Analysis of Graph Signals, edited by Ljubiša Stanković, Ervin Sejdić, (electronic resource)
Publication
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Introduction to Graph Signal Processing -- Oversampled Graph Laplacian Matrix for Graph Filter Banks -- Toward an Uncertainty Principle for Weighted Graphs -- Graph Theoretic Uncertainty and Feasibility -- Signal-Adapted Tight Frames on Graphs -- Local Spectral Analysis of the Cerebral Cortex: New Gyrification Indices -- Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets
Dimensions
unknown
Edition
1st ed. 2019.
Extent
1 online resource (516 pages)
Form of item
online
Isbn
9783030035747
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-030-03574-7
Sound
unknown sound
Specific material designation
remote
System control number
  • (CKB)4100000007181329
  • (MiAaPQ)EBC5608255
  • (DE-He213)978-3-030-03574-7
  • (EXLCZ)994100000007181329

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