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1.
A min-max theorem for complex symmetric matrices   总被引:1,自引:0,他引:1  
We optimize the form Re xtTx to obtain the singular values of a complex symmetric matrix T. We prove that for ,
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2.
Let be the set of entrywise nonnegative n×n matrices. Denote by r(A) the spectral radius (Perron root) of . Characterization is obtained for maps such that r(f(A)+f(B))=r(A+B) for all . In particular, it is shown that such a map has the form
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3.
Let be a locally strongly convex hypersurface, given by the graph of a convex function xn+1=f(x1,…,xn) defined in a convex domain ΩRn. M is called a α-extremal hypersurface, if f is a solution of
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Let Ψ be a bounded set of n×n non-negative matrices. Recently, the max algebra version μ(Ψ) of the generalized spectral radius of Ψ was introduced. We show that
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7.
Let A be an n-by-n (n?2) matrix of the form
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8.
Let φ be a positive linear functional on Mn(C) and f,g mutually conjugate in the sense of Young. In this note we show a necessary and sufficient condition for the inequality
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9.
The paper deals with an entire matrix-valued function of a complex argument (an entire matrix pencil) f of order ρ(f)<. Identities for the following sums of the characteristic values of f are established:
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10.
Given a bounded set Ψ of n×n non-negative matrices, let ρ(Ψ) and μ(Ψ) denote the generalized spectral radius of Ψ and its max version, respectively. We show that
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11.
It is known that for any nonzero complex n×n matrices X and Y the quotient of Frobenius norms
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13.
We show that if A is an n-by-n (n?3) matrix of the form
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14.
Let f(t) be a non-negative concave function on the positive half-line. Given an arbitrary partitioned positive semi-definite matrix, we show that
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15.
The aim of this paper is to establish the convergence of the block iteration methods such as the block successively accelerated over-relaxation method (BAOR) and the symmetric block successively accelerated over-relaxation method (BSAOR): Let be a weak block H-matrix to partition π, then for ,
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16.
Let T be an n×n matrix. The Davis-Wielandt shell of T is defined as the set
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17.
In this paper, we obtain the following upper bound for the largest Laplacian graph eigenvalue λ(G):
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18.
Dunkl and Williams showed that for any nonzero elements x,y in a normed linear space X
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19.
Traditionally an inverse eigenvalue problem is about reconstructing a matrix from a given spectral data. In this work we study the set of real matrices A of order n such that the linear complementarity system
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20.
In this paper we consider the one-dimensional p-Laplacian boundary value problem on time scales
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