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Condition: acceptable. Readable copy. Pages may have considerable notes highlighting. May have varying covers. Fast Shipping - Mailed in plastic mailer!
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Time-Frequency Based Feature Extraction and Classification
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Condition: New.
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Time-Frequency Based Feature Extraction and Classification: Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Condition: New.
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Time-Frequency Based Feature Extraction and Classification: Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Condition: New.
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Time-Frequency Based Feature Extraction and Classification: Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 85.78
US$ 16.17 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Time-Frequency Based Feature Extraction and Classification
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 88.45
US$ 20.25 shipping
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Vertex-Frequency Analysis of Graph Signals (Signals and Communication Technology)
Book 155 of 180: Signals and Communication TechnologySeller: Riverby Books (DC Inventory), Fredericksburg, VA, U.S.A.
Seller rating 5 out of 5 stars
hardcover. Condition: Good. Hardcover without dust jacket. Bound in glossy pictorial paper over boards with white lettering on the covers and spine. Minor wear to back cover, but book remains in overall very good condition. Binding is tight and secure. Corners are slightly bumped. Pages are crisp, clean and bright. Springer. No date on title page. Copyright page dated 2019. 507 pages. A good copy. We ship everyday from a real neighborhood bookstore. This description is written by an actual person, who is holding the book in front of them to make sure it?s properly described. Please contact us with questions or if you would like to see photographs.
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Multimedia Signals and Systems: Basic and Advanced Algorithms for Signal Processing
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 131.12
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Hardcover. Condition: Very Good. 1st Edition. Oversized hardcover, weight: 1840g (please note: extra shipping will be required), xviii + 605 pages, NOT ex-library. Printed and bound in the UK. Interior is clean and bright throughout, with unmarked text, free of inscriptions and stamps, firmly bound. Boards show shelfwear, scuff-marks, rubbed tip of lower outer corner of the front board. Issued without a dust jacket. -- Contents: Preface; Editors; Contributors; I Introduction -- 1. Signal Processing in the Era of Biomedical Big Data / Tiago H. Falk & Ervin Sejdic; 2. Collecting and Making Sense of Big Data for Improved Health Care / Thomas R. Clancy; 3. Big Data Era in Magnetic Resonance Imaging of the Human Brain / Xiaoyu Ding, Elisabeth de Castro Caparelli & Thomas J. Ross; II Signal Processing for Big Data -- 4. Data-Driven Approaches for Detecting and Identifying Anomalous Data Streams / Shaofeng Zou; 5. Time-Frequency Analysis for EEG Quality Measurement and Enhancement with Applications in Newborn EEG Abnormality Detection Multichannel EEG Enhancement and Classification for Newborn Health Outcome Prediction / Boualem Boashash; 6. Active Recursive Bayesian State Estimation for Big Biological Data / Mohammad Moghadamfalahi, Murat Akcakaya & Deniz Erdogmus; 7. Compressive Sensing Methods for Reconstruction of Big Sparse Signals / Ljubisa Stankovic, Milos Dakovic & Isidora Stankovic; 8. Low-Complexity DCT Approximations for Biomedical Signal Processing in Big Data / Renato J. Cintra; 9. Dynamic Processes on Complex Networks / June Zhang & José M.F. Moura; 10. Modeling Functional Networks via Piecewise-Stationary Graphical Models / Hang Yu & Justin Dauwels; 11. Topological Data Analysis of Biomedical Big Data / Angkoon Phinyomark, Esther Ibañez-Marcelo & Giovanni Petri; 12. Targeted Learning with Application to Health Care Research / Susan Gruber; III Applications of Signal Processing and Machine Learning for Big Biomedical Data -- 13. Scalable Signal Data Processing for Measuring Functional Connectivity in Epilepsy Neurological Disorder / Arthur Gershon; 14. Machine Learning Approaches to Automatic Interpretation of EEGs / Iyad Obeid & Joseph Picone; 15. Information Fusion in Deep Convolutional Neural Networks for Biomedical Image Segmentation / Mohammad Havaei; 16. Automated Biventricular Cardiovascular Modelling from MRI for Big Heart Data Analysis / Kathleen Gilbert; 17. Deep Learning for Retinal Analysis / Henry A. Leopold, John S. Zelek & Vasudevan Lakshminarayanan; 18. Dictionary Learning Applications for HEp-2 Cell Classification / Sadaf Monajemi; 19. Computational Sequence- and NGS-Based MicroRNA Prediction / R.J. Peace & James R. Green; 20. Bayesian Classification of Genomic Big Data / Ulisses M. Braga-Neto; 21. Neuroelectrophysiology of Sleep and Insomnia / Ramiro Chaparro-Vargas; 22. Automated Processing of Big Data in Sleep Medicine / Sara Mariani, Shaun M. Purcell & Susan Redline; 23. Integrating Clinical Physiological Knowledge at the Feature and Classifier Levels in Design of a Clinical Decision Support System for Improved Prediction of Intensive Care Unit Outcome / Ali Jalali; 24. Trauma Outcome Prediction in the Era of Big Data: From Data Collection to Analytics / Shiming Yang, Peter F. Hu & Colin F. Mackenzie; 25. Enhancing Medical Problem Solving through the Integration of Temporal Abstractions with Bayesian Networks in Time-Oriented Clinical Domains / Kalia Orphanou, Athena Stassopoulou & Elpida Keravnou; 26. Big Data in Critical Care Using Artemis / Carolyn McGregor; 27. Improving Neurorehabilitation of the Upper Limb through Big Data / José Zariffa; 28. Multimodal Ambulatory Fall Risk Assessment in the Era of Big Data / Mina Nouredanesh & James Tung; Index.
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Condition: New. pp. 391.
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Add to basketHardcover. Condition: Brand New. 2nd edition. 9.25x6.25x1.25 inches. In Stock.
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Vertex-Frequency Analysis of Graph Signals (Signals and Communication Technology)
Book 155 of 180: Signals and Communication TechnologySeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 186.74
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Time-Frequency Based Feature Extraction and Classification
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 187.70
US$ 20.25 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Time-Frequency Based Feature Extraction and Classification: Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
US$ 176.59
US$ 33.75 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Like New. Like New. book.
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US$ 179.37
US$ 33.75 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: Like New. Like New. book.
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Time-Frequency Based Feature Extraction and Classification
Language: English
Published by VDM Verlag Dr. Müller, 2009
ISBN 10: 3639219600 ISBN 13: 9783639219609
Condition: As New. Unread book in perfect condition.
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Multimedia Signals and Systems
Language: English
Published by Springer-Verlag GmbH, 2012
ISBN 10: 1461442079 ISBN 13: 9781461442073
Condition: Sehr gut. Zustand: Sehr gut | Seiten: 322 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Signal Processing and Machine Learning for Biomedical Big Data
Language: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498773451 ISBN 13: 9781498773454
Condition: New.
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Vertex-frequency Analysis Of Graph Sign
Book 155 of 180: Signals and Communication TechnologySeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Signal Processing and Machine Learning for Biomedical Big Data
Language: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498773451 ISBN 13: 9781498773454
US$ 251.83
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Vertex-Frequency Analysis of Graph Signals
Book 155 of 180: Signals and Communication TechnologyLanguage: English
Published by Springer International Publishing, 2018
ISBN 10: 3030035735 ISBN 13: 9783030035730
Buch. Condition: 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. 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.
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Signal Processing and Machine Learning for Biomedical Big Data
Language: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498773451 ISBN 13: 9781498773454
Condition: New.
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Condition: New.
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Add to basketHardcover. Condition: Brand New. 524 pages. 9.25x6.10x1.22 inches. In Stock.
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Add to basketHardcover. Condition: New. New. book.
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Signal Processing and Machine Learning for Biomedical Big Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 293.57
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Ships from United Kingdom to U.S.A.Quantity: 10 available
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