2017
DOI: 10.3934/dcdsb.2017210
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Continuous and discrete one dimensional autonomous fractional ODEs

Abstract: In this paper, we study 1D autonomous fractional ODEs D γ c u = f (u), 0 < γ < 1, where u : [0, ∞) → R is the unknown function and D γ c is the generalized Caputo derivative introduced by Li and Liu ( arXiv:1612.05103). Based on the existence and uniqueness theorem and regularity results in previous work, we show the monotonicity of solutions to the autonomous fractional ODEs and several versions of comparison principles. We also perform a detailed discussion of the asymptotic behavior for f (u) = Au p . In pa… Show more

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Cited by 24 publications
(43 citation statements)
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“…However, for H = 0.8 or α = 0.4, the mean square distance has a rapid drop at the early stage, but then the memory lingers for long time so that the convergence is very slow. This is also the case for normal fractional ODE [37]. In fact, in Fig.…”
Section: A Numerical Simulationsupporting
confidence: 65%
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“…However, for H = 0.8 or α = 0.4, the mean square distance has a rapid drop at the early stage, but then the memory lingers for long time so that the convergence is very slow. This is also the case for normal fractional ODE [37]. In fact, in Fig.…”
Section: A Numerical Simulationsupporting
confidence: 65%
“…By the theory in [37], u(·) is nondecreasing and thus R n ≤ 0. Consequently, applying Theorem 3.1 (4), we have u(t n ) ≤ u n .…”
Section: Properties Of the Discretizationmentioning
confidence: 99%
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“…Proof. Assume first without loss of generality that one of the inequalities in (17) and (18) is strict, say C D α 0+ m 2 (t) < L(m 2 (t)) and m 2 (0) < m 0 ≤ m 1 (0). We will show that m 2 (t) < m 1 (t) for all t ∈ [0, T ].…”
Section: Proof Using the Same Arguments As In [25 Lemma 21]mentioning
confidence: 99%