tailieunhanh - báo cáo hóa học:" Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions | Boundary Value Problems SpringerOpen0 This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text HTML versions will be made available soon. Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions Boundary Value Problems 2012 2012 2 doi 1687-2770-2012-2 WeiYuan Zhang ahzwy@ JunMin Li jmli@ ISSN 1687-2770 Article type Research Submission date 25 October 2011 Acceptance date 13 January 2012 Publication date 13 January 2012 Article URL http content 2012 1 2 This peer-reviewed article was published immediately upon acceptance. It can be downloaded printed and distributed freely for any purposes see copyright notice below . For information about publishing your research in Boundary Value Problems go to http authors instructions For information about other SpringerOpen publications go to http 2012 Zhang and Li licensee Springer. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions WeiYuan Zhang 1 2 and JunMin Li1 1School of Science Xidian University Shaan Xi Xi an 710071 . China 2Institute of Maths and Applied Mathematics Xianyang Normal University Xianyang ShaanXi 712000 . China Corresponding author ahzwy@ Email address JML jmli@ Abstract In this article a delay-differential equation modeling a bidirectional associative memory BAM neural networks NNs with reaction-diffusion terms is investigated. A feedback control law is derived to achieve the state global .