| Description |
1 online resource |
| Contents |
Part 1. State-of-the-art surveys & original matrix theory work: -- Supremum/Infimum and Nonlinear Averaging of Positive Definite Symmetric Matrices / Jesús Angulo -- The Riemannian Mean of Positive Matrices / Rajendra Bhatia -- The Geometry of Low-Rank Kalman Filters / Silvère Bonnabel and Rodolphe Sepulchre -- KV Cohomology in Information Geometry / Michel Nguiffo Boyom and Paul Mirabeau Byande -- Derivatives of Multilinear Functions of Matrices / Priyanka Grover -- Jensen Divergence-Based Means of SPD Matrices / Frank Nielsen, Meizhu Liu and Baba C. Vemuri -- Exponential Barycenters of the Canonical Cartan Connection and Invariant Means on Lie Groups / Xavier Pennec and Vincent Arsigny |
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Part 2. Advanced matrix theory for radar processing: -- Medians and Means in Riemannian Geometry: Existence, Uniqueness and Computation / Marc Arnaudon, Frédéric Barbaresco and Le Yang -- Information Geometry of Covariance Matrix: Cartan-Siegel Homogeneous Bounded Domains, Mostow/Berger Fibration and Fréchet Median / Frédéric Barbaresco -- On the Use of Matrix Information Geometry for Polarimetric SAR Image Classification / Pierre Formont, Jean-Philippe Ovarlez and Frédéric Pascal -- Doppler Information Geometry for Wake Turbulence Monitoring / Zhongxun Liu and Frédéric Barbaresco |
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Part 3. Matrix-based signal processing applications: -- Review of the Application of Matrix Information Theory in Video Surveillance / M K Bhuyan and Malathi T -- Comparative Evaluation of Symmetric SVD Algorithms for Real-Time Face and Eye Tracking / Tapan Pradhan, Aurobinda Routray and Bibek Kabi -- Real-Time Detection of Overlapping Sound Events with Non-Negative Matrix Factorization / Arnaud Dessein, Arshia Cont and Guillaume Lemaitre -- Mining Matrix Data with Bregman Matrix Divergences for Portfolio Selection / Richard Nock, Brice Magdalou, Eric Briys and Frank Nielsen -- Learning Mixtures by Simplifying Kernel Density Estimators / Olivier Schwander and Frank Nielsen -- Particle Filtering on Riemannian Manifolds. Application to Covariance Matrices Tracking / Hichem Snoussi |
| Summary |
This book is an outcome of the Indo-French Workshop on Matrix Information Geometries (MIG): Applications in Sensor and Cognitive Systems Engineering, which was held in Ecole Polytechnique and Thales Research and Technology Center, Palaiseau, France, in February 23-25, 2011. The workshop was generously funded by the Indo-French Centre for the Promotion of Advanced Research (IFCPAR). During the event, 22 renowned invited french or indian speakers gave lectures on their areas of expertise within the field of matrix analysis or processing. From these talks, a total of 17 original contribution or state-of-the-art chapters have been assembled in this volume. All articles were thoroughly peer-reviewed and improved, according to the suggestions of the international referees. The 17 contributions presented are organized in three parts: (1) State-of-the-art surveys & original matrix theory work, (2) Advanced matrix theory for radar processing, and (3) Matrix-based signal processing applications |
| Analysis |
Engineering |
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Remote sensing |
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Data mining |
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Matrix theory |
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Signal, Image and Speech Processing |
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Linear and Multilinear Algebras, Matrix Theory |
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Mathematical Applications in Computer Science |
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Remote Sensing/Photogrammetry |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
| Subject |
Signal processing -- Digital techniques -- Mathematics -- Congresses
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Matrix analytic methods -- Congresses
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Geometric analysis -- Congresses
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TECHNOLOGY & ENGINEERING -- Mechanical.
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Ingénierie.
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Geometric analysis
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Matrix analytic methods
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Signal processing -- Digital techniques -- Mathematics
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Nielsen, Frank
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Bhatia, Rajendra, 1952-
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| ISBN |
9783642302329 |
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3642302327 |
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9781283630115 |
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1283630117 |
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