Numerical simulations and complex valued fractional order neural networks via ([formula omitted] – μ)-uniformly contractive mappings

Abstract

In this article, we present some fixed point results for (ɛ−μ)-uniformly contractive mappings and Ćirić–Riech–Rus type (ɛ−μ)-uniformly locally contractive mappings. As an application, the fixed point approach in suprametric spaces is used to examine the uniform stability problem of fractional-order complex-valued neural networks with time delay and equilibrium point results for impulsive fractional-order complex-valued neural networks with time delay. In addition, we used topological concepts such as compactness, closed convex sets, etc. instead of the traditional method that would have been used in the literature for many years. A few numerical results are provided to show the feasibility and correctness of the results presented.