https://doi.org/10.1140/epjp/s13360-023-04823-3
Regular Article
Dynamical analysis and implementation of novel discrete memristive chaotic maps with hidden attractors
1
School of Physics, Central South University, 410083, Changsha, China
2
School of Electronic Information, Central South University, 410083, Changsha, China
Received:
23
October
2023
Accepted:
21
December
2023
Published online:
6
January
2024
Memristors have brought new driving force to the development of chaos theory for their intrinsic nonlinearity. Thus, it becomes an attractive research topic to build novel memristive chaotic maps with simple structure and high complexity. In this paper, we present a class of novel memristive chaotic maps based on a simple modulo operation, and the feature of no fixed points can be robustly controlled in the proposed memristive model. By several numerical methods, the rich dynamical performances of the proposed memristive maps are investigated, such as wide chaotic range, large Lyapunov exponent (LE), high complexity, low iteration time and very few periodic windows. Notably, setting appropriate control parameters can further improve the performances of the proposed memristive maps. Moreover, they display hidden coexisting attractors with extreme uniform distribution, which accommodates to many important chaos-based applications. To evaluate the actual overall performances of the memristive chaotic maps, we develop a digital circuit platform to obtain their attractors, and test their chaotic sequences with finite precision effect by the National Institute of Standards and Technology (NIST) test.
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