Applied and computational matrix analysis : MAT-TRIAD, Coimbra, Portugal, September 2015 Selected, revised contributions /

Applied and computational matrix analysis : MAT-TRIAD, Coimbra, Portugal, September 2015 Selected, revised contributions /

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Bibliographic Details
Meeting name:MAT-TRIAD (Conference) (6th : 2015 : Combra, Portugal)
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource (xiii, 347 pages) : illustrations (some color)
Language:English
Series:Springer proceedings in mathematics & statistics, 2194-1009 ; volume 192
Springer proceedings in mathematics & statistics ; v. 192.
Subject:
Matrix analytic methods -- Congresses.
Matrix analytic methods.
Conference papers and proceedings.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11272258
Hidden Bibliographic Details
Other authors / contributors:Bebiano, Natália, editor.
ISBN:9783319499840
331949984X
9783319499826
3319499823
Digital file characteristics:text file
PDF
Notes:Includes index.
Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed March 9, 2017).
Summary:This volume presents recent advances in the field of matrix analysis based on contributions at the MAT-TRIAD 2015 conference. Topics covered include interval linear algebra and computational complexity, Birkhoff polynomial basis, tensors, graphs, linear pencils, K-theory and statistic inference, showing the ubiquity of matrices in different mathematical areas. With a particular focus on matrix and operator theory, statistical models and computation, the International Conference on Matrix Analysis and its Applications 2015, held in Coimbra, Portugal, was the sixth in a series of conferences. Applied and Computational Matrix Analysis will appeal to graduate students and researchers in theoretical and applied mathematics, physics and engineering who are seeking an overview of recent problems and methods in matrix analysis.
Other form:Print version: MAT-TRIAD (Conference) (6th : 2015 : Combra, Portugal). Applied and computational matrix analysis. Cham, Switzerland : Springer, 2017 3319499823
Standard no.:10.1007/978-3-319-49984-0
Table of Contents:
  • 1. A. Amiraslani, H. Faßbender, N. Shayanfar: Birkhoff polynomial basis
  • 2. M. Hladik: On relation between P-matrices and regularity of interval matrices
  • 3. J. Horacek, M. Hladik, M. Cerny: Interval Linear Algebra and Computational Complexity
  • 4. P. Almeida, D. Napp, R. Pinto: On optimal extended row distance profile
  • 5. M. El Oued, D. Napp, R. Pinto, M. Toste: The dual of convolutional codes over Zpr
  • 6. S. Mendes: On the K-theory of the reduced C*-algebras of GL(n, R) and GL(n, C)
  • 7. D. Moreira Cardoso, S.J. Pinheiro: Spectral bounds for the k-regular induced subgraph problem
  • 8. K. Toyonaga, C. Johnson, R. Uhrig: Multiplicities: Adding a Vertex to a Graph
  • 9. M. Bendaoud, M. Jabbar, M. Sarih: Nonlinear local invertibility preservers
  • 10. A. Kovacec: More on the Hankel Pencil Conjecture
  • 11. P. Batra: Componentwise products of totally nonnegative matrices generated by functions in the Laguerre-Polya class
  • 12. N. Bebiano, J. da Providencia, A. Nata, J.P. da Providencia: Fields of values of linear pencils and spectral inclusion regions
  • 13. N. Bebiano, J. da Providencia, F. Esmaeili: The characteristic polynomial of linear pencils of small size and the numerical range
  • 14. H.K. Duru, D. Bozkurt: Integer Powers of Certain Complex Pentadiagonal Toeplitz Matrices
  • 15. R. Mamede: Chains and antichains in the Bruhat order for classes of (0,1)-matrices
  • 16. M. Saha: Iterative method for linear system with coefficient matrix as an Mv-matrix
  • 17. C. Gamas: Symmetrized tensors and spherical functions
  • 18. J. Pielaszkiewicz, D. von Rosen, M. Singull: Testing independence via spectral moments
  • 19. R. Kala, A. Markiewicz, S. Puntanen: Some further remarks on the linear sufficiency in the linear model
  • 20. L.M. Grilo, C.A. Coelho: The exact and near-exact distributions for the statistic used to test the reality of covariance matrix in a complex normal distribution
  • 21. A. Silva, M. Fonseca, J. Mexia: Variance Components Estimation in Mixed Linear Model.

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