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Solving a system of nonlinear difference equations with bilinear dynamics

  • Received: 11 October 2024 Revised: 11 November 2024 Accepted: 14 November 2024 Published: 03 December 2024
  • MSC : 39A10, 40A05

  • This paper presented a comprehensive study of a three-dimensional nonlinear system of difference equations, which can be reduced to a two-dimensional bilinear system. The system monitored the evolution of three sequences $ \left(P_{m}\right), $ $ \left(Q_{m}\right), $ $ \left(R_{m}\right) $, governed by recursive relations. We investigated the solvability of this system and provided general closed-form solutions for various parameter conditions. Furthermore, the simulations provided valuable insights into the dynamic behavior of animals, modeled using recursive difference equations. The model encapsulated essential behavioral metrics, represented by the variables $ P $, $ Q $, and $ R $, which corresponded to individual actions, social interactions, and environmental stressors, respectively. These variables adapted dynamically in response to internal and external influences, illustrating the system's sensitivity to various behavioral and environmental conditions.

    Citation: Hashem Althagafi, Ahmed Ghezal. Solving a system of nonlinear difference equations with bilinear dynamics[J]. AIMS Mathematics, 2024, 9(12): 34067-34089. doi: 10.3934/math.20241624

    Related Papers:

  • This paper presented a comprehensive study of a three-dimensional nonlinear system of difference equations, which can be reduced to a two-dimensional bilinear system. The system monitored the evolution of three sequences $ \left(P_{m}\right), $ $ \left(Q_{m}\right), $ $ \left(R_{m}\right) $, governed by recursive relations. We investigated the solvability of this system and provided general closed-form solutions for various parameter conditions. Furthermore, the simulations provided valuable insights into the dynamic behavior of animals, modeled using recursive difference equations. The model encapsulated essential behavioral metrics, represented by the variables $ P $, $ Q $, and $ R $, which corresponded to individual actions, social interactions, and environmental stressors, respectively. These variables adapted dynamically in response to internal and external influences, illustrating the system's sensitivity to various behavioral and environmental conditions.



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