首页|Hybrid tri-memristor hyperchaotic map and application in Wasserstein Generative Adversarial Nets

Hybrid tri-memristor hyperchaotic map and application in Wasserstein Generative Adversarial Nets

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Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic systems.To investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-memristor hyperchaotic(HTMH)mapping structures based on the hybrid parallel/cascade and cascade/parallel operations,respectively.Taking the HTMH mapping structure with hybrid parallel/cascade operation as an example,this map possesses a spatial invariant set whose stability is closely related to the initial states of the memristors.Dynamics distributions and bifurcation behaviours dependent on the control parameters are explored with numerical tools.Specifically,the memristor initial offset-boosting mechanism is theore-tically demonstrated,and memristor initial offset-boosting behaviours are numerically verified.The results clarify that the HTMH map can exhibit hyperchaotic behaviours and extreme multistability with homogeneous coexisting infinite attractors.In addition,an FPGA hardware platform is fabricated to implement the HTMH map and generate pseudorandom numbers(PRNs)with high randomness.Notably,the generated PRNs can be applied in Wasserstein generative adversarial nets(WGANs)to enhance training stability and generation capability.

memristorhybrid tri-memristor mapspatial invariant sethyperchaosextreme multistabilitygenerative adversarial nets

GU Yang、BAO Han、YU XiHong、HUA ZhongYun、BAO BoCheng、XU Quan

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School of Microelectronics and Control Engineering,Changzhou University Changzhou 213159,China

School of Computer Science and Technology,Harbin Institute of Technology Shenzhen 518055,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaScientific Research Foundation of Jiangsu Provincial Education Department of China

62271088622010946207114222KJB510001

2024

10.1007/s11431-023-2613-9

中国科学:技术科学(英文版)
中国科学院

中国科学:技术科学(英文版)

CSTPCDEI
影响因子：1.056
ISSN：1674-7321
年,卷(期)：2024.67(6)