• DocumentCode
    1758289
  • Title

    The Field of Values of a Matrix and Neural Networks

  • Author

    Georgiou, George M.

  • Author_Institution
    Sch. of Comput. Sci. & Eng., California State Univ., San Bernardino, CA, USA
  • Volume
    25
  • Issue
    9
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    1613
  • Lastpage
    1620
  • Abstract
    The field of values of a matrix, also known as the numerical range, is introduced in the context of neural networks. Using neural network techniques, an algorithm and a generalization are developed that find eigenpairs of a normal matrix. The dynamics of the algorithm can be observed on the complex plane. Only limited visualization is possible in the case when the matrix is Hermitian (or real symmetric) since the field of values is confined on the real line. The eigenpairs can serve as stored memories, which are recalled by using the algorithm. Shifting in the algorithm is also discussed, which assists in finding other eigenpairs. Trajectories of runs of the algorithm are visually presented, through which the behavior of the algorithms is elucidated.
  • Keywords
    Hermitian matrices; eigenvalues and eigenfunctions; neural nets; numerical analysis; Hermitian matrix; algorithm dynamics; algorithm run trajectories; complex plane; eigenpairs; matrix field-of-values; neural network techniques; normal matrix; numerical range; real line; real symmetric matrix; shifting process; stored memories; Eigenvalues and eigenfunctions; Manganese; Matrix decomposition; Neural networks; Symmetric matrices; Trajectory; Vectors; Complex-valued neural networks; eigenvalues; eigenvectors; field of values; normal matrices; numerical range; numerical range.;
  • fLanguage
    English
  • Journal_Title
    Neural Networks and Learning Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2162-237X
  • Type

    jour

  • DOI
    10.1109/TNNLS.2013.2293287
  • Filename
    6733348