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Periodic solutions and stationary distribution for a stochastic predator-prey system with impulsive perturbations

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  • Lu, Chun
  • Ding, Xiaohua

Abstract

In this paper, we consider a stochastic predator-prey system with Beddington-DeAngelis functional response and impulsive perturbations. First, we prove that the model admits a unique global positive solution by constructing the equivalent system without impulsive perturbations. Second, we establish a sufficient condition which allows the existence of a positive periodic solution using stochastic Lyapunov functions. Finally, for the predator-prey system with Beddington-DeAngelis functional response disturbed by both white noise and telephone noise, we give the sufficient conditions for the stationary distribution which is ergodic and positive recurrent of the solution. The conclusion implies that the stochastic system has a positive T-periodic Markov process in a certain condition when the corresponding deterministic system has at least one positive T-periodic solution.

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  • Lu, Chun & Ding, Xiaohua, 2019. "Periodic solutions and stationary distribution for a stochastic predator-prey system with impulsive perturbations," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 313-322.
    • Handle: RePEc:eee:apmaco:v:350:y:2019:i:c:p:313-322
    DOI: 10.1016/j.amc.2019.01.023
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    References listed on IDEAS

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    1. Zu, Li & Jiang, Daqing & O’Regan, Donal & Hayat, Tasawar & Ahmad, Bashir, 2018. "Ergodic property of a Lotka–Volterra predator–prey model with white noise higher order perturbation under regime switching," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 93-102.
    2. Mao, Xuerong & Marion, Glenn & Renshaw, Eric, 2002. "Environmental Brownian noise suppresses explosions in population dynamics," Stochastic Processes and their Applications, Elsevier, vol. 97(1), pages 95-110, January.
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    Cited by:

    1. Zhao, Xin & Zeng, Zhijun, 2020. "Stationary distribution of a stochastic predator–prey system with stage structure for prey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
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    3. Lu, Chun, 2021. "Dynamics of a stochastic Markovian switching predator–prey model with infinite memory and general Lévy jumps," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 181(C), pages 316-332.
    4. Yang, Jiangtao, 2022. "Periodic measure of a stochastic non-autonomous predator–prey system with impulsive effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 464-479.
    5. Lu, Chun & Liu, Honghui & Zhang, De, 2021. "Dynamics and simulations of a second order stochastically perturbed SEIQV epidemic model with saturated incidence rate," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    6. Lu, Chun, 2022. "Dynamical analysis and numerical simulations on a crowley-Martin predator-prey model in stochastic environment," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    7. Rajchakit, G. & Sriraman, R. & Vignesh, P. & Lim, C.P., 2021. "Impulsive effects on Clifford-valued neural networks with time-varying delays: An asymptotic stability analysis," Applied Mathematics and Computation, Elsevier, vol. 407(C).

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