2022
DOI: 10.1007/s13540-022-00029-z
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Unified predictor–corrector method for fractional differential equations with general kernel functions

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Cited by 28 publications
(11 citation statements)
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“…It is also worth noting that the results in this paper can be extended to semilinear cases, and many fractional neural network equations hold such a structure. Recently, Wu et al [20][21][22] studied the conclusions of general fractional calculus, and put forward a numerical method to solve fractional differential equations and fractional delay differential equations with general kernels, respectively. Moreover, Wu et al [23] gave a uniform delayed Mittag-Leffler function without segmented definition which is helpful to analyze the basic properties of the solution, such as monotonicity, differentiability and so on.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…It is also worth noting that the results in this paper can be extended to semilinear cases, and many fractional neural network equations hold such a structure. Recently, Wu et al [20][21][22] studied the conclusions of general fractional calculus, and put forward a numerical method to solve fractional differential equations and fractional delay differential equations with general kernels, respectively. Moreover, Wu et al [23] gave a uniform delayed Mittag-Leffler function without segmented definition which is helpful to analyze the basic properties of the solution, such as monotonicity, differentiability and so on.…”
Section: Discussionmentioning
confidence: 99%
“…The study of such problems is very meaningful. Furthermore, we may consider some new problems by combining the ideas of references [20][21][22][23].…”
Section: Discussionmentioning
confidence: 99%
“…which says that the controllability Grammian [ ] G 1, 2 is +ve definite and, by theorem 3.2, the linear part of (15)…”
Section: Numerical Examplesmentioning
confidence: 99%
“…Aydi et al examined the existence and uniqueness of positive solutions for a fractional thermostat model for both cases of concave and convex source terms by utilizing ψ-Caputo fractional derivative in [9]. For reference, [10][11][12][13][14][15][16] these are certain articles on differential equations that heavily rely on the ψ-Caputo fractional derivative.…”
Section: Introductionmentioning
confidence: 99%
“…etc. Recently, some scholars have paid much attention to theories and applications such as Laplace transform [8] and predictor-corrector method [27]. Moreover, the physical meaning of the kernel function g(t) are explained by use of continuous time random walk theory [4], and the boundedness condition is provided to guarantee that the general fractional integral is well defined [3].…”
Section: Introductionmentioning
confidence: 99%