Title :
Existence of Periodic Solution for High-Order Neural Networks with Neutral Delay
Author :
Tang, Mei-Lan ; Liu, Xin-Ge
Author_Institution :
Sch. of Math. Sci. & Comput. Technol., Central South Univ., Changsha
Abstract :
In this paper, high-order neural networks with neutral delay are considered. Based on the continuation theorem of coincidence degree theory and a priori estimate, new result on the existence of periodic solution for delayed high-order Hopfield-type neural networks with neutral delay is established. The result of this paper is new and it complements previously known results. An illustrative example is given to demonstrate the effectiveness of our result.
Keywords :
neural nets; high-order neural networks; neutral delay; periodic solution; Artificial neural networks; Biological neural networks; Biomedical signal processing; Chaos; Computer networks; Delay effects; Delay estimation; Hopfield neural networks; Neural networks; Stability; continuation theorem; high-order neural networks; neutral delay; periodic solution; priori estimate;
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.2008.7
