Stability of Periodic Orbits in Dynamic Binary Neural Networks with Ternary Connection

摘要

This paper studies dynamic binary neural networks that can generate various periodic orbits. The networks is characterized by signum activation function and ternary connection parameters. In order to analyze the dynamics, we present two simple feature quantities that characterize plentifulness of transient phenomena and superstability of the periodic orbits. Calculating the feature quantities for a class of networks, we investigate transient and superstability of the periodic orbits.