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
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