  In this paper, Cohen-Grossberg neural networks with unpredictable and
compartmental periodic unpredictable strengths of connectivity between cells
and inputs are investigated. To approve Poisson stability and unpredictability
in neural networks, the method of included intervals and contraction mapping
principle are used. The existence, uniqueness, and exponential stability of
unpredictable and Poisson stable outputs are discussed. Examples with numerical
simulations that support the theoretical results are provided. The dependence
of the neural network dynamics on the numerical characteristic, the degree of
periodicity, is shown.
