Generic properties of the lower spectral radius for some low-rank pairs of matrices

被引:3
|
作者
Morris, Ian D.
机构
基金
英国工程与自然科学研究理事会;
关键词
Joint spectral radius; Lower spectral radius; Generalised spectral radius; FINITENESS CONJECTURE; EXPONENTIAL-GROWTH; COUNTEREXAMPLE; SL(2; R);
D O I
10.1016/j.laa.2017.02.023
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The lower spectral radius of a set of d x d matrices is defined to be the minimum possible exponential growth rate of long products of matrices drawn from that set. When considered as a function of a finite set of matrices of fixed cardinality it is known that the lower spectral radius can vary discontinuously as a function of the matrix entries. In a previous article the author and J. Bochi conjectured that when considered as a function on the set of all pairs of 2 x 2 real matrices, the lower spectral radius is discontinuous on a set of positive (eight-dimensional) Lebesgue measure, and related this result to an earlier conjecture of Bochi and Fayad. In this article we investigate the continuity of the lower spectral radius in a simplified context in which one of the two matrices is assumed to be of rank one. We show in particular that the set of discontinuities of the lower spectral radius on the set of pairs of 2 x 2 real matrices has positive seven-dimensional Lebesgue measure, and that among the pairs of matrices studied, the finiteness property for the lower spectral radius is true on a set of full Lebesgue measure but false on a residual set. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:35 / 60
页数:26
相关论文
共 50 条
  • [1] Some structural properties of low-rank matrices related to computational complexity
    Codenotti, B
    Pudlák, P
    Resta, G
    THEORETICAL COMPUTER SCIENCE, 2000, 235 (01) : 89 - 107
  • [2] SOME PROPERTIES OF THE SPECTRAL RADIUS OF A SET OF MATRICES
    Czornik, Adam
    Jurgas, Piotr
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2006, 16 (02) : 183 - 188
  • [3] Generalized low-rank approximation of matrices based on multiple transformation pairs
    Ahmadi, Soheil
    Rezghi, Mansoor
    PATTERN RECOGNITION, 2020, 108 (108)
  • [4] Recovery of low-rank matrices based on the rank null space properties
    Gao, Yi
    Han, Xuanli
    Ma, Mingde
    INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2017, 15 (04)
  • [5] Some lower bounds for the spectral radius of matrices using traces
    Wang, Lin
    Xu, Mao-Zhi
    Huang, Ting-Zhu
    LINEAR ALGEBRA AND ITS APPLICATIONS, 2010, 432 (04) : 1007 - 1016
  • [6] Low-rank and sparse matrices fitting algorithm for low-rank representation
    Zhao, Jianxi
    Zhao, Lina
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2020, 79 (02) : 407 - 425
  • [7] REDUCED BASIS METHODS: FROM LOW-RANK MATRICES TO LOW-RANK TENSORS
    Ballani, Jonas
    Kressner, Daniel
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2016, 38 (04): : A2045 - A2067
  • [8] Low-Rank Spectral Learning
    Kulesza, Alex
    Rao, N. Raj
    Singh, Satinder
    ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 33, 2014, 33 : 522 - 530
  • [9] EUCLIDEAN REPRESENTATION OF LOW-RANK MATRICES AND ITS GEOMETRIC PROPERTIES
    Xie, Fangzheng
    SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2023, 44 (02) : 822 - 866
  • [10] Matrices with Hierarchical Low-Rank Structures
    Ballani, Jonas
    Kressner, Daniel
    EXPLOITING HIDDEN STRUCTURE IN MATRIX COMPUTATIONS: ALGORITHMS AND APPLICATIONS, 2016, 2173 : 161 - 209