Random Graphs for Statistical Pattern Recognition

Author:   David J. Marchette (Naval Surface Warfare Center, Dahlgren, VA, USA)
Publisher:   John Wiley & Sons Inc
ISBN:  

9780471221760


Pages:   264
Publication Date:   12 March 2004
Format:   Hardback
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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Random Graphs for Statistical Pattern Recognition


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Full Product Details

Author:   David J. Marchette (Naval Surface Warfare Center, Dahlgren, VA, USA)
Publisher:   John Wiley & Sons Inc
Imprint:   Wiley-Interscience
Dimensions:   Width: 16.20cm , Height: 2.30cm , Length: 24.90cm
Weight:   0.572kg
ISBN:  

9780471221760


ISBN 10:   0471221767
Pages:   264
Publication Date:   12 March 2004
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface. Acknowledgments. 1. Preliminaries. 1.1 Graphs and Digraphs. 1.2 Statistical Pattern Recognition. 1.3 Statistical Issues. 1.4 Applications. 1.5 Further Reading. 2. Computational Geometry. 2.1 Introduction. 2.2 Voronoi Cells and Delaunay Triangularization. 2.3 Alpha Hulls. 2.4 Minimum Spanning Trees. 2.5 Further Reading. 3. Neighborhood Graphs. 3.1 Introduction. 3.2 Nearest-Neighbor Graphs. 3.3 k-Nearest Neighbor Graphs. 3.4 Relative Neighborhood Graphs. 3.5 Gabriel Graphs. 3.6 Application: Nearest Neighbor Prototypes. 3.7 Sphere of Influence Graphs. 3.8 Other Relatives. 3.9 Asymptotics. 3.10 Further Reading. 4. Class Cover Catch Digraphs. 4.1 Catch Digraphs. 4.2 Class Covers. 4.3 Dominating Sets. 4.4 Distributional Results for Cn,m-graphs. 4.5 Characterizations. 4.6 Scale Dimension. 4.7 (α,β) Graphs 4.8 CCCD Classification. 4.9 Homogeneous CCCDs. 4.10 Vector Quantization. 4.11 Random Walk Version. 4.12 Further Reading. 5. Cluster Catch Digraphs. 5.1 Basic Definitions. 5.2 Dominating Sets. 5.3 Connected Components. 5.4 Variable Metric Clustering. 6. Computational Methods. 6.1 Introduction. 6.2 Kd-Trees. 6.3 Class Cover Catch Digraphs. 6.4 Cluster Catch Digraphs. 6.5 Voroni Regions and Delaunay Triangularizations. 6.6 Further Reading. References. Author Index. Subject Index.

Reviews

...constructed...as a book on random graphs, this is quite a good one. (Journal of the American Statistical Association, September 2006) ...I recommend this book to those who...wish to explore the exciting place where graph theory and pattern recognition meet. (Statistics in Medical Research, October 2005) This well-written book presents practical tools, and information that was previously found scattered in various journals. (Computing Reviews.com, March 9, 2005) ...an excellent resource book that would be a valuable addition... (Technometrics, February 2005) ...clearly and accessible written, and nicely conveys the power, breadth and applicability of some very elegant ideas... (Short Book Reviews, Vol.24, No.3, December 2004) Buy this book if use graphs in cluster and classification analysis. (Journal of Classification, Vol.21, No.2, 2004)


?constructed?as a book on random graphs, this is quite a good one. (Journal of the American Statistical Association, September 2006) ?I recommend this book to those who...wish to explore the exciting place where graph theory and pattern recognition meet. (Statistics in Medical Research, October 2005) This well-written book presents practical tools, and information that was previously found scattered in various journals. (Computing Reviews.com, March 9, 2005) ?an excellent resource book that would be a valuable addition? (Technometrics, February 2005) ??clearly and accessible written, and nicely conveys the power, breadth and applicability of some very elegant ideas...? (Short Book Reviews, Vol.24, No.3, December 2004) ?Buy this book if use graphs in cluster and classification analysis.? (Journal of Classification, Vol.21, No.2, 2004)


?constructed?as a book on random graphs, this is quite a good one. (Journal of the American Statistical Association, September 2006) ?I recommend this book to those who...wish to explore the exciting place where graph theory and pattern recognition meet. (Statistics in Medical Research, October 2005) This well-written book presents practical tools, and information that was previously found scattered in various journals. (Computing Reviews.com, March 9, 2005) ?an excellent resource book that would be a valuable addition? (Technometrics, February 2005) ??clearly and accessible written, and nicely conveys the power, breadth and applicability of some very elegant ideas...? (Short Book Reviews, Vol.24, No.3, December 2004) ?Buy this book if use graphs in cluster and classification analysis.? (Journal of Classification, Vol.21, No.2, 2004)


Author Information

DAVID J. MARCHETTE, PhD, is a researcher at the Naval Surface Warfare Center in Dahlgren, Virginia, where he investigates computational statistics and pattern recognition, primarily as it applies to image processing, automatic target recognition, and computer security. He is also an adjunct professor at George Mason University and a lecturer at Johns Hopkins University.

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