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Table of Contents
Intro
About Rao and Lal
Foreword
Preface
Acknowledgements
Contents
Editors and Contributors
1 On Some Matrix Versions of Covariance, Harmonic Mean and Other Inequalities: An Overview
1.1 Introduction
1.2 Covariance Inequalities
1.3 Harmonic Mean Inequalities
1.4 General Mean Inequalities
References
2 The Impact of Prof. C. R. Rao's Research Used in Solving Problems in Applied Probability
2.1 Professor Rao's Research on Generalized Matrix Inverses
2.2 Professor Hunter Is Exposed to Prof. Rao's Research
2.3 Professor Hunter's Applications of Prof. Rao's Research in the Field of Applied Probability
2.4 Professor Hunter's Links with Prof. Rao
2.5 Final Comments
References
3 Upper Bounds for the Euclidean Distances Between the BLUEs Under the Partitioned Linear Fixed Model and the Corresponding Mixed Model
3.1 Introduction
3.2 Upper Bounds for the BLUEs
3.3 Upper Bounds Related to OLSE
3.4 Conclusions
References
4 Nucleolus Computation for Some Structured TU Games via Graph Theory and Linear Algebra
4.1 TU Cooperative Game
4.2 Nucleolus for the Talmud Game ch4AM
4.3 The Core and Balanced Collection
4.4 The Lexicographic Center ch4MPS
4.5 Assignment Games ch4NOL
4.6 Domination Power Between Married Couple
4.6.1 The Kernel/Nucleolus of a Standard Tree Game ch4GM1996
4.6.2 Balanced Connected Games ch4SAD1998
4.6.3 Nucleolus for Cyclic Permutation Games ch4SRT2005,ch4TP1984
4.6.4 Brief Remarks on Some References Included
References
5 From Linear System of Equations to Artificial Intelligence-The Evolution Journey of Computer Tomographic Image Reconstruction Algorithms
5.1 Introduction
5.2 From Filtered Back Projection to Iterative Reconstruction Technique to Clinical Necessity
5.3 Reconstruction Algorithms as Inverse Problems
5.4 Compressed Sensing-Based CT Image Reconstruction Algorithms
5.5 Nyquist Sampling Versus Non-uniform Sampling
5.6 Current and Future Developments
5.7 Conclusion and Open Question
References
6 Shapley Value and Other Axiomatic Extensions to Shapley Value
6.1 Shapley Value
6.2 Multi-choice Shapley Value (ch6HsiaospsRaghavansps1993sps)
6.3 Potential Function and Shapley Value (ch6Hartsps1988sps)
References
7 An Accelerated Block Randomized Kaczmarz Method
7.1 Introduction
7.2 Randomized Kaczmarz Method
7.3 Block Accelerated RK
7.4 Convergence and Error
7.5 Applications to Tensor Equations
7.5.1 Tensor BARK
7.5.2 Tensor BARK in the Fourier Domain
7.6 Numerical Examples
7.6.1 Comparison Between ARK and BARK
7.6.2 T-BARK Performance
References
8 Nullity of Graphs-A Survey and Some New Results
8.1 Basic Results on Nullity
8.2 Bounds for the Nullity of a Graph
8.3 Energy and Nullity
8.4 Graphs with Nullity 0 and 1
8.5 Graph Operations Preserving Nullity
About Rao and Lal
Foreword
Preface
Acknowledgements
Contents
Editors and Contributors
1 On Some Matrix Versions of Covariance, Harmonic Mean and Other Inequalities: An Overview
1.1 Introduction
1.2 Covariance Inequalities
1.3 Harmonic Mean Inequalities
1.4 General Mean Inequalities
References
2 The Impact of Prof. C. R. Rao's Research Used in Solving Problems in Applied Probability
2.1 Professor Rao's Research on Generalized Matrix Inverses
2.2 Professor Hunter Is Exposed to Prof. Rao's Research
2.3 Professor Hunter's Applications of Prof. Rao's Research in the Field of Applied Probability
2.4 Professor Hunter's Links with Prof. Rao
2.5 Final Comments
References
3 Upper Bounds for the Euclidean Distances Between the BLUEs Under the Partitioned Linear Fixed Model and the Corresponding Mixed Model
3.1 Introduction
3.2 Upper Bounds for the BLUEs
3.3 Upper Bounds Related to OLSE
3.4 Conclusions
References
4 Nucleolus Computation for Some Structured TU Games via Graph Theory and Linear Algebra
4.1 TU Cooperative Game
4.2 Nucleolus for the Talmud Game ch4AM
4.3 The Core and Balanced Collection
4.4 The Lexicographic Center ch4MPS
4.5 Assignment Games ch4NOL
4.6 Domination Power Between Married Couple
4.6.1 The Kernel/Nucleolus of a Standard Tree Game ch4GM1996
4.6.2 Balanced Connected Games ch4SAD1998
4.6.3 Nucleolus for Cyclic Permutation Games ch4SRT2005,ch4TP1984
4.6.4 Brief Remarks on Some References Included
References
5 From Linear System of Equations to Artificial Intelligence-The Evolution Journey of Computer Tomographic Image Reconstruction Algorithms
5.1 Introduction
5.2 From Filtered Back Projection to Iterative Reconstruction Technique to Clinical Necessity
5.3 Reconstruction Algorithms as Inverse Problems
5.4 Compressed Sensing-Based CT Image Reconstruction Algorithms
5.5 Nyquist Sampling Versus Non-uniform Sampling
5.6 Current and Future Developments
5.7 Conclusion and Open Question
References
6 Shapley Value and Other Axiomatic Extensions to Shapley Value
6.1 Shapley Value
6.2 Multi-choice Shapley Value (ch6HsiaospsRaghavansps1993sps)
6.3 Potential Function and Shapley Value (ch6Hartsps1988sps)
References
7 An Accelerated Block Randomized Kaczmarz Method
7.1 Introduction
7.2 Randomized Kaczmarz Method
7.3 Block Accelerated RK
7.4 Convergence and Error
7.5 Applications to Tensor Equations
7.5.1 Tensor BARK
7.5.2 Tensor BARK in the Fourier Domain
7.6 Numerical Examples
7.6.1 Comparison Between ARK and BARK
7.6.2 T-BARK Performance
References
8 Nullity of Graphs-A Survey and Some New Results
8.1 Basic Results on Nullity
8.2 Bounds for the Nullity of a Graph
8.3 Energy and Nullity
8.4 Graphs with Nullity 0 and 1
8.5 Graph Operations Preserving Nullity