On minimizing the largest eigenvalue of a symmetric matrix

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Invertibility and Largest Eigenvalue of Symmetric Matrix Signings

The spectra of signed matrices have played a fundamental role in social sciences, graph theory, and control theory. In this work, we investigate the computational problems of identifying symmetric signings of matrices with natural spectral properties. Our results are twofold: 1. We show NP-completeness for the following three problems: verifying whether a given matrix has a symmetric signing th...

متن کامل

On the largest eigenvalue of a symmetric nonnegative tensor

In this paper, some important spectral characterizations of symmetric nonnegative tensors are analyzed. In particular, it is shown that a symmetric nonnegative tensor has the following properties: (i) its spectral radius is zero if and only if it is a zero tensor; (ii) it is weakly irreducible (respectively, irreducible) if and only if it has a unique positive (respectively, nonnegative) eigenv...

متن کامل

On lower bounds for the largest eigenvalue of a symmetric matrix

We consider lower bounds for the largest eigenvalue of a symmetric matrix. In particular we extend a recent approach by Piet Van Mieghem. © 2008 Elsevier Inc. All rights reserved. AMS classification: Primary 15A42; Secondary 30B10

متن کامل

Minimizing the Profile of a Symmetric Matrix

New approaches are developed for minimizing the profile of a sparse, symmetric matrix. The heuristic approaches seek to minimize the profile growth, either absolutely or in a weighted sense. The exchange methods make a series of permutations in an initial ordering to strictly improve the profile. Comparisons with the spectral algorithm, a level structure method, and a wave front method are pres...

متن کامل

Estimating the Largest Eigenvalue of a Positive Definite Matrix

The power method for computing the dominant eigenvector of a positive definite matrix will converge slowly when the dominant eigenvalue is poorly separated from the next largest eigenvalue. In this note it is shown that in spite of this slow convergence, the Rayleigh quotient will often give a good approximation to the dominant eigenvalue after a very few iterations-even when the order of the m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Linear Algebra and its Applications

سال: 1995

ISSN: 0024-3795

DOI: 10.1016/0024-3795(93)00068-b