Complex dynamics of a new multiscroll memristive neural network

Chen Y., Lai Q., Zhang Y., Erkan U., TOKTAŞ A.

Nonlinear Dynamics, cilt.112, sa.10, ss.8603-8616, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 112 Sayı: 10
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s11071-024-09466-2
  • Dergi Adı: Nonlinear Dynamics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.8603-8616
  • Anahtar Kelimeler: Chaos, Circuit implementation, Coexisting attractors, Memristive neural network, Multi-scroll attractors
  • Ankara Üniversitesi Adresli: Evet

Özet

In this paper, a cyclic memristive neural network structure is proposed. There are counterclockwise connections between the neurons. The system generates a controllable number of multi-scroll chaos by means of memristors with multi-segment nonlinear functions, which can produce a controllable infinite coexistence of heterogeneous attractors with initial offsets and a large range of amplitude-modulation properties. Through numerical simulations, the phenomenon of multi-scroll chaos is demonstrated and the coexisting attractors are found to exhibit extreme multi-stability as well as parameter-dependent amplitude-modulation properties. In addition, the feasibility of the system is verified by the construction of the circuit platform, the results of the digital hardware experiments are given, and the PRNG is constructed by applying this circular memristor neural network system.