Abstract
BAM fuzzy cellular neural networks with time-varying delays in leakage terms and impulses are considered. Some sufficient conditions for the exponential stability of the networks are established by using differential inequality techniques. The results of this paper are completely new and complementary to the previously known results. Finally, an example is given to demonstrate the effectiveness and conservativeness of our theoretical results.
Highlights
The bidirectional associative memory (BAM) neural networks were first introduced by Kosko [1–3]
We will give some sufficient conditions to guarantee the exponential stability of system (3)
We consider a class of BAM fuzzy cellular neural networks with time-varying delays in leakage terms and impulses
Summary
The bidirectional associative memory (BAM) neural networks were first introduced by Kosko [1–3]. Very little attention has been paid to neural networks with time delay in the leakage (or “forgetting”) term [24–30]. In [31], the authors studied the following BAM fuzzy cellular network with time delay in leakage terms and discrete and unbounded distributed delays:. It is desirable to study the fuzzy BAM neural networks with time-varying delays in leakage terms. In [32], by using a fixed point theorem and differential inequality techniques, the authors studied the existence and exponential stability of equilibrium point for the following BAM neural network with time-varying delays in leakage terms on time scales: xiΔ (t) = −aixi (t − δi (t)) + ∑cjifj (yj (t − τji (t))). Very few results are available on exponential stability of equilibrium point for fuzzy BAM neural networks with time-varying delays in leakage terms and impulses.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
