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
Link To Document :
بازگشت