NOVEL EXPONENTIAL STABILITY CONDITIONS FOR A CLASS OF INTERVAL PROJECTION NEURAL NETWORKS
2009 ◽
Vol 02
(03)
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pp. 287-297
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Keyword(s):
In this paper, a class of interval projection neural networks for solving quadratic programming problems are investigated. By using Gronwall inequality and constructing appropriate Lyapunov functionals, several novel conditions are derived to guarantee the exponential stability of the equilibrium point. Compared with previous results, the conclusions obtained here are suitable not only to convex quadratic programming problems but also to degenerate quadratic programming problems, and the conditions are more weaker than the earlier results reported in the literature. In addition, one numerical example is discussed to illustrate the validity of the main results.
2004 ◽
Vol 14
(05)
◽
pp. 337-345
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1997 ◽
Vol 95
(3)
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pp. 615-635
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Keyword(s):
1993 ◽
Vol 46-47
(2)
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pp. 509-539
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2010 ◽
Vol 20
(05)
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pp. 1541-1549
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2009 ◽
Vol 19
(06)
◽
pp. 449-456
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1999 ◽
Vol 11
(1-4)
◽
pp. 671-681
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2009 ◽
Vol 43
(1)
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pp. 145-161
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