DocumentCode
1402835
Title
Comments on "New conditions for global stability of neural networks with application to linear and quadratic programming problems"
Author
Liang, Xue-Bin ; Wu, Li-De
Author_Institution
Dept. of Comput. Sci., Fudan Univ., Shanghai, China
Volume
44
Issue
11
fYear
1997
Firstpage
1099
Lastpage
1101
Abstract
For original paper, see M. Forti and A. Tesi, ibid., vol. 42, pp. 354-66 (1995). This letter makes the following comments: 1) the assumption of all neuron activation functions to vanish at the origin, which is utilized in the proof of the result implying the existence and uniqueness of the network equilibrium point, can be actually omitted; 2) in the infinite sector case, the result of global asymptotic stability (GAS) remains true with respect to the class of increasing (not necessarily strictly) activations, as in the finite sector case. Consequently, a result about absolute stability (ABST) of neural networks, which can represent a generalization of the existing related ones, is also obtained.
Keywords
absolute stability; asymptotic stability; linear programming; neural nets; nonlinear differential equations; quadratic programming; stability criteria; absolute stability; finite sector case; global asymptotic stability; global stability conditions; infinite sector case; linear programming problems; network equilibrium point; neural networks; neuron activation functions; nonlinear differential equations; quadratic programming problems; Circuits; Design methodology; Digital filters; Finite impulse response filter; Frequency; IIR filters; Low pass filters; Neural networks; Signal processing; Stability;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/81.641813
Filename
641813
Link To Document