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Inequalities: Theory of Majorization and Its Applications
I Theory of Majorization
1 Introduction 3
A Motivation and Basic Definitions . . . . . . . . . . 3
B Majorization as a Partial Ordering . . . . . . . . . 18
C Order-Preserving Functions . . . . . . . . . . . . . 19
D Various Generalizations of Majorization . . . . . . . 21
2 Doubly Stochastic Matrices 29
A Doubly Stochastic Matrices and Permutation
Matrices . . . . . . . . . . . . . . . . . . . . . . . . 29
B Characterization of Majorization Using Doubly
StochasticMatrices . . . . . . . . . . . . . . . . . . 32
C Doubly Substochastic Matrices and Weak
Majorization . . . . . . . . . . . . . . . . . . . . . . 36
D Doubly Superstochastic Matrices and Weak
Majorization . . . . . . . . . . . . . . . . . . . . . . 42
E Orderings on D . . . . . . . . . . . . . . . . . . . . 45
F Proofs of Birkhoff’s Theorem and Refinements . . . 47
G Classes of Doubly Stochastic Matrices . . . . . . . . 52
xvii
xviii Contents
H More Examples of Doubly Stochastic and Doubly
Substochastic Matrices . . . . . . . . . . . . . . . . 61
I Properties of Doubly Stochastic Matrices . . . . . . 67
J Diagonal Equivalence of Nonnegative Matrices . . . 76
3 Schur-Convex Functions 79
A Characterization of Schur-Convex Functions . . . . 80
B Compositions Involving Schur-Convex Functions . . 88
C Some General Classes of Schur-Convex Functions . 91
D Examples I. Sums of Convex Functions . . . . . . . 101
E Examples II. Products of Logarithmically
Concave (Convex) Functions . . . . . . . . . . . . . 105
F Examples III. Elementary Symmetric Functions . . 114
G Muirhead’s Theorem . . . . . . . . . . . . . . . . . 120
H Schur-Convex Functions on D and Their
Extension to Rn . . . . . . . . . . . . . . . . . . . 132
I Miscellaneous Specific Examples . . . . . . . . . . . 138
J Integral Transformations Preserving
Schur-Convexity . . . . . . . . . . . . . . . . . . . . 145
K Physical Interpretations of Inequalities . . . . . . . 153
4 Equivalent Conditions