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Complex-valued neural networks with time delays in the Lp sense: Numerical simulations and finite time stability

Author

Listed:
  • Panda, Sumati Kumari
  • Vijayakumar, Velusamy
  • Nagy, A.M.

Abstract

A discrete fractional-order complex-valued neural network is taken into consideration in the present study. For the existence of the solution of the considered model to be stable in finite time, certain requirements are specified. Our strategy focuses on the use of the recently formulated discrete fractional calculus, mathematical inequalities, Krasnoselskii’s fixed point theorem, and the Arzelà–Ascoli theorem. We present afew numerical examples that demonstrate the theoretical results’ implementation.

Suggested Citation

  • Panda, Sumati Kumari & Vijayakumar, Velusamy & Nagy, A.M., 2023. "Complex-valued neural networks with time delays in the Lp sense: Numerical simulations and finite time stability," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:chsofr:v:177:y:2023:i:c:s0960077923011657
    DOI: 10.1016/j.chaos.2023.114263
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