Sigmoidal approximations of a delay neural lattice model with Heaviside functions
Xiaoli Wang, Meihua Yang, Peter E. Kloeden · Communications on Pure & Applied Analysis · 2020
The approximation of Heaviside coefficient functions in delay neural lattice models with delays by sigmoidal functions is investigated. The solutions of the delay sigmoidal models are shown to converge to a solution of the delay differential inclusion as the sigmoidal parameter goes to zero. In addition, the existence of global attractors is established and compared for the various systems.