DocumentCode
1326145
Title
Stability and relaxation time of Tank and Hopfield´s neural network for solving LSE problems
Author
Yan, Hong
Author_Institution
Sch. of Electr. Eng., Sydney Univ., NSW, Australia
Volume
38
Issue
9
fYear
1991
fDate
9/1/1991 12:00:00 AM
Firstpage
1108
Lastpage
1110
Abstract
A.D. Culhane et al. (1989) proposed a fast technique for computing discrete Hartley and Fourier transforms using a Tank and Hopfield linear programming neural network. It was proved mathematically that the network is stable under some conditions. The network can also be used for solving linear least squares error (LSE) problems. It is shown that the stability of the network is guaranteed even under weaker conditions. The author also provides a more accurate solution for the network relaxation constants and discusses the accuracy of computation
Keywords
least squares approximations; linear programming; mathematics computing; neural nets; stability criteria; LSE problems; Tank/Hopfield neural network; linear least squares error; linear programming; network relaxation constants; relaxation time; stability; Circuit stability; Circuits and systems; Computer networks; DH-HEMTs; Eigenvalues and eigenfunctions; Equations; Hopfield neural networks; Least squares methods; Linear programming; Neural networks;
fLanguage
English
Journal_Title
Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0098-4094
Type
jour
DOI
10.1109/31.83886
Filename
83886
Link To Document