Title :
Periodic Solution of Stochastic Recurrent Neural Networks with Delays
Author :
Wan, Li ; Zhou, Qinghua
Author_Institution :
Dept. of Math. & Phys., Wuhan Univ. of Sci. & Eng., Wuhan
Abstract :
The periodic solution for stochastic recurrent neural networks (RNNs) with delays is studied. By constructing suitable Lyapunov functionals and employing nonnegative semimartingale convergence theorem, the delay-independent sufficient conditions to guarantee the existence and uniqueness of periodic solution are obtained.
Keywords :
Lyapunov methods; convergence; delays; recurrent neural nets; Lyapunov functionals; delays; nonnegative semimartingale convergence theorem; periodic solution; stochastic recurrent neural networks; Biological neural networks; Cellular neural networks; Computer networks; Delay effects; Mathematics; Neurons; Neurotransmitters; Recurrent neural networks; Stochastic processes; Sufficient conditions;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.65
