New robust stability results for bidirectional associative memory neural networks with multiple time delays

作者：Senan Sibel^*; Arik Sabri; Liu Derong

来源：Applied Mathematics and Computation, 2012, 218(23): 11472-11482.

DOI：10.1016/j.amc.2012.04.075

• Equilibrium and stability analysis
• Bidirectional associative memory neural networks
• Lyapunov functionals

In this paper, the robust stability problem is investigated for a class of bidirectional associative memory (BAM) neural networks with multiple time delays. By employing suitable Lyapunov functionals and using the upper bound norm for the interconnection matrices of the neural network system, some novel sufficient conditions ensuring the existence, uniqueness and global robust stability of the equilibrium point are derived. The obtained results impose constraint conditions on the system parameters of neural network independent of the delay parameters. Some numerical examples and simulation results are given to demonstrate the applicability and effectiveness of our results, and to compare the results with previous robust stability results derived in the literature.

• 出版日期2012-8-1