More is more: The benefits of denser sensor deployment
Matthew P. Johnson, Deniz Sariöz, et al.
INFOCOM 2009
We present some new global stability results of neural networks with delay and show that these results generalize recently published stability results. In particular, several different stability conditions in the literature which were proved using different Lyapunov functionals are generalized and unified by proving them using the same Lyapunov functional. We also show that under certain conditions, reversing the directions of the coupling between neurons preserves the global asymptotical stability of the neural network. © 2005, The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Matthew P. Johnson, Deniz Sariöz, et al.
INFOCOM 2009
Chai Wah Wu
ISCAS 2011
Chai Wah Wu
IEEE TACON
Dan Chevion, Ehud D. Karnin, et al.
TAGA 2004