2014
DOI: 10.2478/s11534-014-0460-0
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Delay-induced state transition and resonance in periodically driven tumor model with immune surveillance

Abstract: Abstract:The phenomenon of stochastic resonance (SR) in a tumor growth model under the presence of immune surveillance is investigated. Time delay and cross-correlation between multiplicative and additive noises are considered in the system. The signal-to-noise ratio (SNR) is calculated when periodic signal is introduced multiplicatively. Our results show that: (i) the time delay can accelerate the transition from the state of stable tumor to that of extinction, however the correlation between two noises can a… Show more

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Cited by 6 publications
(6 citation statements)
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“…In particular, the time delay τ can even make the tumor cells go into extinction. In other words, it is found that a weak Finally, the results in the present paper and the ones in [38] are compared. The stochastic tumor model is written as x…”
Section: Discussionmentioning
confidence: 65%
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“…In particular, the time delay τ can even make the tumor cells go into extinction. In other words, it is found that a weak Finally, the results in the present paper and the ones in [38] are compared. The stochastic tumor model is written as x…”
Section: Discussionmentioning
confidence: 65%
“…ω Nevertheless, [38] considers the case of the negative multiplicative periodic signal A t cos( ). the term of time delay in [38] is x t x t ( ) ( ).…”
Section: ( ) Cos( )]mentioning
confidence: 99%
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“…For a long time in the past, the study of dynamical systems has often ignored the inherent time delay in the system, and with the ever-increasing requirements for system accuracy, the effect of time delay on the system is becoming more and more non-negligible. Biologically, the proliferation process of tumor cells does not occur instantaneously, and the periodic treatment is not immediate, so the effect of time delay should be considered when studying the growth process of tumor cells [44][45][46][47][48][49]. Alberto et al [46] investigated the stability and Hopf bifurcation of the immobile point of a delayed tumor growth model.…”
Section: Introductionmentioning
confidence: 99%