A statistical neural network olfactory model is proposed. The model is a simple generalization of the Hopfield neural network system. Retrieval properties are analysed and the zero temperature mean field phase diagram is obtained.
We consider a Hopfield neural network system containing discrete as well
as distributed delays. A stability result of arbitrary type is proved
under weaker assumptions than the used ones so far. This result includes
exponential and polynomial (or power type) stability as special cases.
Our proof relies on a judicious choice of Lyapunov-type functionals and
some appropriate manipulations.
Arbitrary stability for a Hopfield neural network problem with discrete and distributed delays
