Parameter Control Methods for Discrete Memristive Maps with Network Structure
Yuan Fang, Shuting Zhang, Guibin Xing, Yue Deng
Abstract
Discrete memristors (DMs) have attracted increasing interest in recent years and can be applied in chaotic circuits and neuromorphic systems. To better enrich and enhance the kinetics and performance of DM maps, this article introduces two improved control methods to construct a series of DM maps with different network typologies by coupling DM seed maps. Some specific examples are demonstrated to back up these methods. Due to the effect and specific constructs of memristors, the new coupling DM maps will have infinite invariant points with higher dimensions, whose advantages of larger parameter space and expended chaotic ranges are evaluated by dynamic simulations. Besides, to investigate the application of the proposed methods, these new DM maps are implemented on the DSP platform, and the pseudorandom number generator is designed, as well as their high randomness is indicated by the strict test results.