Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains

Abstract

The work considers the μ-p.a.a. (measure-pseudo almost automorphic) solutions of MAM neural network with neuron gains. By using the properties of μ-p.a.a. functions, inequality technique and Banach contraction mapping principle, some sufficient conditions are obtained to ensure the existence and the global exponential stability of a unique μ-p.a.a. solution of MAM neural network with neuron gains. Moreover, some numerical examples are given to illustrate our main results.

Keywords

• Banach fixed point theorem
• MAM neural network
• Globally exponential stability
• Measure-pseudo almost automorphic
• Neuron gains