The main aim of the book is to present various types of neural networks
and their stability properties illustrated by simulations. It is given
several discrete models such as Hopfield-type delay impulsive neural
networks, neural networks with non-instantaneous impulses and delays,
and several continuous neural networks with switching topologies at
impulsive times both deterministic as well as random. It is discussed
different types of stability properties of the considered models. Also,
it is studied the leader-following consensus problem for discrete
multi-agent system with non-instantaneous impulses. Most of the
theoretical results are illustrated by computer simulations. The study
in the book is motivated by the potential applications of neural
networks. It required the definitions and study of models which can more
adequate describe the behavior in multi-agent systems. Much of the
material presented in this book is based on the recent research of
authors on the topic. The current book is intended for a wide audience,
including Mathematicians, Applied Researchers, and Practitioners, whose
interest extends beyond the boundaries of qualitative analysis of neural
networks.