Two-Dimensional Discrete Memristive Oscillatory Hyperchaotic Maps with Diverse Dynamics

IEEE Trans Ind Electron（2025）

East China Jiaotong Univ | City Univ Hong Kong

Cited 0|Views10

Abstract

Discrete memristor (DM) has been extensively used to enhance the complexity of simple chaotic maps due to its special nonlinearity. Yet, the chaotic properties inherent to DM have not been thoroughly explored. This article introduces a simple oscillatory term to the DM model and constructs four hyperchaotic maps. In these maps, the coupling of the ideal DM with the oscillatory term results in maps without fixed points, generating hidden hyperchaotic attractors. The introduction of the oscillatory term into DMs exhibits diverse dynamical behaviors, including coexisting bistable attractors, infinitely many homogeneously coexisting attractors, heterogeneously coexisting attractors, and symmetrically coexisting attractors. The performances of the sequences generated by these maps are evaluated, and they are successfully applied to the design of pseudorandom number generators (PRNGs). The research results demonstrate that the outputs of all four maps, as well as the pseudorandom numbers generated by the PRNG, exhibit high randomness. Finally, a hardware platform is constructed to successfully implement these maps.

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Key words

Memristors,Voltage,Hysteresis,Logistics,Mathematical models,Hardware,Couplings,Coexisting attractor,discrete memristor,hardware device,hyperchaos,pseudorandom number generator (PRNG)

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
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【要点】：本文提出了一种引入振荡项的二维离散忆阻器模型，构建了四种具有多样化动态特性的超混沌映射，并应用于伪随机数生成器设计，表现出高随机性。

【方法】：通过在离散忆阻器模型中引入振荡项，构建了四种不同的超混沌映射，并分析了这些映射的动态特性。

【实验】：使用四种超混沌映射进行伪随机数生成，并在硬件平台上实现了这些映射，数据集名称未提及，但实验结果显示生成的序列具有高随机性。