Research article Special Issues

Analytical results for positivity of discrete fractional operators with approximation of the domain of solutions


  • We study the monotonicity method to analyse nabla positivity for discrete fractional operators of Riemann-Liouville type based on exponential kernels, where (CFRc0θF)(t)>ϵΛ(θ1)(F)(c0+1) such that (F)(c0+1)0 and ϵ>0. Next, the positivity of the fully discrete fractional operator is analyzed, and the region of the solution is presented. Further, we consider numerical simulations to validate our theory. Finally, the region of the solution and the cardinality of the region are discussed via standard plots and heat map plots. The figures confirm the region of solutions for specific values of ϵ and θ.

    Citation: Pshtiwan Othman Mohammed, Donal O'Regan, Dumitru Baleanu, Y. S. Hamed, Ehab E. Elattar. Analytical results for positivity of discrete fractional operators with approximation of the domain of solutions[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 7272-7283. doi: 10.3934/mbe.2022343

    Related Papers:

    [1] Pshtiwan Othman Mohammed, Hari Mohan Srivastava, Sarkhel Akbar Mahmood, Kamsing Nonlaopon, Khadijah M. Abualnaja, Y. S. Hamed . Positivity and monotonicity results for discrete fractional operators involving the exponential kernel. Mathematical Biosciences and Engineering, 2022, 19(5): 5120-5133. doi: 10.3934/mbe.2022239
    [2] Pshtiwan Othman Mohammed, Christopher S. Goodrich, Aram Bahroz Brzo, Dumitru Baleanu, Yasser S. Hamed . New classifications of monotonicity investigation for discrete operators with Mittag-Leffler kernel. Mathematical Biosciences and Engineering, 2022, 19(4): 4062-4074. doi: 10.3934/mbe.2022186
    [3] Maysaa Al Qurashi, Saima Rashid, Sobia Sultana, Hijaz Ahmad, Khaled A. Gepreel . New formulation for discrete dynamical type inequalities via $ h $-discrete fractional operator pertaining to nonsingular kernel. Mathematical Biosciences and Engineering, 2021, 18(2): 1794-1812. doi: 10.3934/mbe.2021093
    [4] M. Botros, E. A. A. Ziada, I. L. EL-Kalla . Semi-analytic solutions of nonlinear multidimensional fractional differential equations. Mathematical Biosciences and Engineering, 2022, 19(12): 13306-13320. doi: 10.3934/mbe.2022623
    [5] Jian Huang, Zhongdi Cen, Aimin Xu . An efficient numerical method for a time-fractional telegraph equation. Mathematical Biosciences and Engineering, 2022, 19(5): 4672-4689. doi: 10.3934/mbe.2022217
    [6] Tahir Khan, Roman Ullah, Gul Zaman, Jehad Alzabut . A mathematical model for the dynamics of SARS-CoV-2 virus using the Caputo-Fabrizio operator. Mathematical Biosciences and Engineering, 2021, 18(5): 6095-6116. doi: 10.3934/mbe.2021305
    [7] Ritu Agarwal, Pooja Airan, Mohammad Sajid . Numerical and graphical simulation of the non-linear fractional dynamical system of bone mineralization. Mathematical Biosciences and Engineering, 2024, 21(4): 5138-5163. doi: 10.3934/mbe.2024227
    [8] Noura Laksaci, Ahmed Boudaoui, Seham Mahyoub Al-Mekhlafi, Abdon Atangana . Mathematical analysis and numerical simulation for fractal-fractional cancer model. Mathematical Biosciences and Engineering, 2023, 20(10): 18083-18103. doi: 10.3934/mbe.2023803
    [9] H. M. Srivastava, Khaled M. Saad, J. F. Gómez-Aguilar, Abdulrhman A. Almadiy . Some new mathematical models of the fractional-order system of human immune against IAV infection. Mathematical Biosciences and Engineering, 2020, 17(5): 4942-4969. doi: 10.3934/mbe.2020268
    [10] Debao Yan . Existence results of fractional differential equations with nonlocal double-integral boundary conditions. Mathematical Biosciences and Engineering, 2023, 20(3): 4437-4454. doi: 10.3934/mbe.2023206
  • We study the monotonicity method to analyse nabla positivity for discrete fractional operators of Riemann-Liouville type based on exponential kernels, where (CFRc0θF)(t)>ϵΛ(θ1)(F)(c0+1) such that (F)(c0+1)0 and ϵ>0. Next, the positivity of the fully discrete fractional operator is analyzed, and the region of the solution is presented. Further, we consider numerical simulations to validate our theory. Finally, the region of the solution and the cardinality of the region are discussed via standard plots and heat map plots. The figures confirm the region of solutions for specific values of ϵ and θ.



    The construction of discrete fractional sums and differences from the knowledge of samples of their corresponding continuous integrals and derivatives arises in the context of discrete fractional calculus; see [1,2,3,4,5,6] for more details. Recently, discrete fractional operators with more general forms of their kernels and properties have gathered attention in both areas of physics and mathematics; see [7,8,9,10].

    In discrete fractional calculus theory, we say that F is monotonically increasing at a time step t if the nabla of F is non-negative, i.e., (F)(t):=F(t)F(t1)0 for each t in the time scale set Nc0+1:={c0+1,c0+2,}. Moreover, the function F is θmonotonically increasing (or decreasing) on Nc0 if F(t+1)>θF(t)(orF(t+1)<θF(t)) for each tNa). In [11,12] the authors considered 1monotonicity analysis for standard discrete Riemann-Liouville fractional differences defined on N0 and in [13] the authors generalized the above by introducing θmonotonicity increasing and decreasing functions and then obtained some θmonotonicity analysis results for discrete Riemann-Liouville fractional differences defined on N0. In [14,15,16], the authors considered monotonicity and positivity analysis for discrete Caputo, Caputo-Fabrizio and Attangana-Baleanu fractional differences and in [17,18] the authors considered monotonicity and positivity results for abstract convolution equations that could be specialized to yield new insights into qualitative properties of fractional difference operators. In [19], the authors presented positivity and monotonicity results for discrete Caputo-Fabrizo fractional operators which cover both the sequential and non-sequential cases, and showed both similarities and dissimilarities between the exponential kernel case (that is included in Caputo-Fabrizo fractional operators) and fractional differences with other types of kernels. Also in [20] the authors extended the results in [19] to discrete Attangana-Baleanu fractional differences with Mittag-Leffler kernels. The main theoretical developments of monotonicity and positivity analysis in discrete fractional calculus can be found in [21,22,23,24] for nabla differences, and in [25,26,27,28] for delta differences.

    The main idea in this article is to analyse discrete Caputo-Fabrizo fractional differences with exponential kernels in the Riemann-Liouville sense. The results are based on a notable lemma combined with summation techniques. The purpose of this article is two-fold. First we show the positiveness of discrete fractional operators from a theoretical point of view. Second we shall complement the theoretical results numerically and graphically based on the standard plots and heat map plots.

    The plan of the article is as follows. In Section 2 we present discrete fractional operators and the main lemma. Section 3 analyses the discrete fractional operator in a theoretical sense. In Section 4 we discuss our theoretical strategy on standard plots (Subsection 4.1) and heat map plots (Subsection 4.2). Finally, in Section 5 we summarize our findings.

    First we recall the definitions in discrete fractional calculus; see [2,3,5] for more information.

    Definition 2.1. (see [2,Definition 2.24]). Let c0R, 0<θ1, F be defined on Nc0 and Λ(θ)>0 be a normalization constant. Then the following operator

    (CFRc0θF)(t):=Λ(θ)ttr=c0+1F(r)(1θ)tr{tNc0+1},

    is called the discrete Caputo-Fabrizio fractional operator with exponential kernels in the Riemann-Liouville sense CFR, and the following operator

    (CFCc0θF)(t):=Λ(θ)tr=c0+1(rF)(r)(1θ)tr{tNc0+1},

    is called the discrete Caputo-Fabrizo fractional operator with exponential kernels in the Caputo sense CFC.

    Definition 2.2 (see [3]). For F:Nc0κR with κ<θκ+1 and κN0, the discrete nabla CFC and CFR fractional differences can be expressed as follows:

    (CFCc0θF)(t)=(CFCc0θκκF)(t),

    and

    (CFRc0θF)(t)=(CFRc0θκκF)(t),

    respectively, for each tNc0+1.

    The following lemma is essential later.

    Lemma 2.1. Assume that F is defined on Nc0 and 1<θ<2. Then the CFR fractional difference is

    (CFRc0θF)(t)=Λ(θ1){(F)(t)+(1θ)(2θ)tc02(F)(c0+1)+(1θ)t1r=c0+2(rF)(r)(2θ)tr1},

    for each tNc0+2.

    Proof. From Definitions 2.1 and 2.2, the following can be deduced for 1<θ<2:

    (CFRc0θF)(t)=Λ(θ1){tr=c0+1(rF)(r)(2θ)trt1r=c0+1(rF)(r)(2θ)tr1}=Λ(θ1){(F)(t)+t1r=c0+1(rF)(r)[(2θ)tr(2θ)tr1]}=Λ(θ1){(F)(t)+(1θ)(2θ)tc02(F)(c0+1)+(1θ)t1r=c0+2(rF)(r)(2θ)tr1},

    for each tNc0+2.

    In the following theorem, we will show that F is monotonically increasing at two time steps even if (CFRc0θF)(t) is negative at the two time steps.

    Theorem 3.1. Let the function F be defined on Nc0+1, and let 1<θ<2 and ϵ>0. Assume that

    (CFRc0θF)(t)>ϵΛ(θ1)(F)(c0+1)fort{c0+2,c0+3}s.t.(F)(c0+1)0. (3.1)

    If (1θ)(2θ)<ϵ, then (F)(c0+2) and (F)(c0+3) are both nonnegative.

    Proof. From Lemma 2.1 and condition (3.1) we have

    (F)(t)(F)(c0+1)[(1θ)(2θ)tc02+ϵ](1θ)t1r=c0+2(rF)(r)(2θ)tr1, (3.2)

    for each tNc0+2. At t=c0+2, we have

    (F)(c0+2)(F)(c0+1)[(1θ)+ϵ](1θ)c0+1r=c0+2(rF)(r)(2θ)c0+1r=00,

    where we have used (1θ)<(1θ)(2θ)<ϵ and (F)(c0+1)0 by assumption. At t=c0+3, it follows from (3.2) that

    (F)(c0+3)=(F)(c0+1)[(1θ)(2θ)+ϵ](1θ)c0+2r=c0+2(rF)(r)(2θ)c0+2r=(F)(c0+1)0[(1θ)(2θ)+ϵ]<0(1θ)<0(F)(c0+2)00, (3.3)

    as required. Hence the proof is completed.

    Remark 3.1. It worth mentioning that Figure 1 shows the graph of θ(1θ)(2θ) for θ(1,2).

    Figure 1.  Graph of θ(1θ)(2θ) for θ(1,2).

    In order for Theorem 3.1 to be applicable, the allowable range of ϵ is ϵ(0,(2θ)(1θ)) for a fixed θ(1,2)

    Now, we can define the set Hκ,ϵ as follows

    Hκ,ϵ:={θ(1,2):(1θ)(2θ)κc02<ϵ}(1,2),κNc0+3.

    The following lemma shows that the collection {Hκ,ϵ}κ=c0+1 forms a nested collection of decreasing sets for each ϵ>0.

    Lemma 3.1. Let 1<θ<2. Then, for each ϵ>0 and κNc0+3 we have that Hκ+1,ϵHκ,ϵ.

    Proof. Let θHκ+1,ϵ for some fixed but arbitrary κNc0+3 and ϵ>0. Then we have

    (1θ)(2θ)κc01=(1θ)(2θ)(2θ)κc02<ϵ.

    Considering 1<θ<2 and κNc0+3, we have 0<2θ<1. Consequently, we have

    (1θ)(2θ)κc02<ϵ 12θ>1<ϵ.

    This implies that θHκ,ϵ, and thus Hκ+1,ϵHκ,ϵ.

    Now, Theorem 3.1 and Lemma 3.1 lead to the following corollary.

    Corollary 3.1. Let F be a function defined on Nc0+1, θ(1,2) and

    (CFRc0θF)(t)>ϵΛ(θ1)(F)(c0+1)suchthat(F)(c0+1)0, (3.4)

    for each tNsc0+3:={c0+3,c0+4,,s} and some sNc0+3. If θHs,ϵ, then we have (F)(t)0 for each tNsc0+1.

    Proof. From the assumption θHs,ϵ and Lemma 3.1, we have

    θHs,ϵ=Hs,ϵs1κ=c0+3Hκ,ϵ.

    This leads to

    (1θ)(2θ)tc02<ϵ, (3.5)

    for each tNsc0+3.

    Now we use the induction process. First for t=c0+3 we obtain (F)(c0+3)0 directly as in Theorem 3.1 by considering inequalities (Eq 3.4) and (Eq 3.5) together with the given assumption (F)(c0+1)0. As a result, we can inductively iterate inequality (Eq 3.2) to get

    (F)(t)0,

    for each tNsc0+2. Moreover, (F)(c0+1)0 by assumption. Thus, (F)(t)0 for each tNsc0+1 as desired.

    In this section, we consider the methodology for the positivity of F based on previous observations in Theorem 3.1 and Corollary 3.1 in such a way that the initial conditions are known. Later, we will illustrate other parts of our article via standard plots and heat maps for different values of θ and ϵ. The computations in this section were performed with MATLAB software.

    Example 4.1. Considering Lemma 1 with t:=c0+3:

    (CFRc0θF)(c0+3)=Λ(θ1){(F)(c0+3)+(1θ)(2θ)(F)(c0+1)+(1θ)c0+2r=c0+2(rF)(r)(2θ)c0+2r}.

    For c0=0, it follows that

    (CFR0θF)(3)=Λ(θ1){(F)(3)+(1θ)(2θ)(F)(1)+(1θ)2r=2(rF)(r)(2θ)2r}=Λ(θ1){(F)(3)+(1θ)(2θ)(F)(1)+(1θ)(F)(2)}=Λ(θ1){F(3)F(2)+(1θ)(2θ)[F(1)F(0)]+(1θ)[F(2)F(1)]}.

    If we take θ=1.99,F(0)=0,F(1)=1,F(2)=1.001,F(3)=1.005, and ϵ=0.007, we have

    (CFR01.99F)(3)=Λ(0.99){0.004+(0.99)(0.01)(0)+(0.99)(0.001)}=0.0069Λ(0.99)>0.007Λ(0.99)=ϵΛ(0.99)(F)(1).

    In addition, we see that (1θ)(2θ)=0.0099<0.007=ϵ. Since the required conditions are satisfied, Theorem 3.1 ensures that (F)(3)>0.

    In Figure 2, the sets Hκ,0.008 and Hκ,0.004 are shown for different values of κ, respectively in Figure 2a, b. It is noted that Hκ,0.008 and Hκ,0.004 decrease by increasing the values of κ. Moreover, in Figure 2a, the set Hκ,0.008 becomes empty for κ45; however, in Figure 2b, we observe the non-emptiness of the set Hκ,0.004 for many larger values of κ up to 90. We think that the measures of Hκ,0.008 and Hκ,0.004 are not symmetrically distributed when κ increases (see Figure 2a, b). We do not have a good conceptual explanation for why this symmetric behavior is observed. In fact, it is not clear why the discrete nabla fractional difference CFRc0θ seems to give monotonically when θ1 rather than for θ2, specifically, it gives a maximal information when θ is very close to 1 as ϵ0+.

    Figure 2.  Graph of Hκ,ϵ for different values of κ and ϵ.

    In the next figure (Figure 3), we have chosen a smaller ϵ (ϵ=0.001), we see that the set Hκ,0.001 is non-empty for κ>320. This tells us that small choices in ϵ give us a more widely applicable result.

    Figure 3.  Graph of Hκ,ϵ for κN3503 and ϵ=0.001.

    In this part, we introduce the set Hκ:={κ:θHκ,ϵ} to simulate our main theoretical findings for the cardinality of the set Hκ via heat maps in Figure 4ad. In these figures: we mean the warm colors such as red ones and the cool colors such as blue ones. Moreover, the θ values are on the xaxis and ϵ values are on the yaxis. We choose ϵ in the interval [0.00001, 0.0001]. Then, the conclusion of these figures are as follows:

    Figure 4.  The cardinality of Hκ for different values of θ with 0.00001ϵ0.0001 in heat maps.

    ● In Figure 4a when θ(1,2) and Figure 4b when θ(1,1.5), we observe that the warmer colors are somewhat skewed toward θ very close to 1, and the cooler colors cover the rest of the figures for θ above 1.05.

    ● In Figure 4c, d, the warmest colors move strongly towards the lower values of θ, especially, when θ(1,1.05). Furthermore, when as θ increases to up to 1.0368, it drops sharply from magenta to cyan, which implies a sharp decrease in the cardinality of Hκ for a small values of ϵ as in the interval [0.00001, 0.0001].

    On the other hand, for larger values of ϵ, the set Hκ will tend to be empty even if we select a smaller θ in such an interval (1,1.05). See the following Figure 5a, b for more.

    Figure 5.  The cardinality of Hκ for different values of ϵ with 1<θ<1.05 in heat maps.

    In conclusion, from Figures 4 and 5, we see that: For a smaller value of ϵ, the set Hκ,ϵ tends to remain non-empty (see Figure 4), unlike for a larger value of ϵ (see Figure 5). Furthermore, these verify that Corollary 3.1 will be more applicable for 1<θ<1.05 and 0.01<ϵ<0.1 as shown in Figure 4d.

    Although, our numerical data strongly note the sensitivity of the set Hκ when slight increasing in ϵ is observed for θ close to 2 compares with θ close to 1.

    In this paper we developed a positivity method for analysing discrete fractional operators of Riemann-Liouville type based on exponential kernels. In our work we have found that (F)(3)0 when (CFRc0θF)(t)>ϵΛ(θ1)(F)(c0+1) such that (F)(c0+1)0 and ϵ>0. We continue to extend this result for each value of t in Nsc0+1 as we have done in Corollary 3.1.

    In addition we presented standard plots and heat map plots for the discrete problem that is solved numerically. Two of the graphs are standard plots for Hκ,ϵ for different values of κ and ϵ (see Figure 2), and the other six graphs consider the cardinality of Hκ for different values of ϵ and θ (see Figures 4 and 5). These graphs ensure the validity of our theoretical results.

    In the future we hope to apply our method to other types of discrete fractional operators which include Mittag-Leffler and their extensions in kernels; see for example [5,6].

    This work was supported by the Taif University Researchers Supporting Project Number (TURSP-2020/86), Taif University, Taif, Saudi Arabia.

    The authors declare there is no conflict of interest.



    [1] C. Goodrich, A. C. Peterson, Discrete Fractional Calculus, Springer, Berlin, 2015. https://doi.org/10.1007/978-3-319-25562-0
    [2] T. Abdeljawad, D. Baleanu, On fractional derivatives with exponential kernel and their discrete versions, Rep. Math. Phys., 80 (2017), 11–27. https://doi.org/10.1016/S0034-4877(17)30059-9 doi: 10.1016/S0034-4877(17)30059-9
    [3] T. Abdeljawad, Q. M. Al-Mdallal, M. A. Hajji, Arbitrary order fractional difference operators with discrete exponential kernels and applications, Discrete Dyn. Nat. Soc., 2017 (2017). https://doi.org/10.1155/2017/4149320 doi: 10.1155/2017/4149320
    [4] T. Abdeljawad, On Riemann and Caputo fractional differences, Comput. Math. Appl., 62 (2011), 1602–1611. https://doi.org/10.1016/j.camwa.2011.03.036 doi: 10.1016/j.camwa.2011.03.036
    [5] T. Abdeljawad, Different type kernel h–fractional differences and their fractional h–sums, Chaos, Solitons Fractals, 116 (2018), 146–156. https://doi.org/10.1016/j.chaos.2018.09.022 doi: 10.1016/j.chaos.2018.09.022
    [6] P. O. Mohammed, T. Abdeljawad, Discrete generalized fractional operators defined using h-discrete Mittag-Leffler kernels and applications to AB fractional difference systems, Math. Methods Appl. Sci., (2020), 1–26, https://doi.org/10.1002/mma.7083 doi: 10.1002/mma.7083
    [7] G. C. Wu, M. K. Luo, L. L. Huang, S. Banerjee, Short memory fractional differential equations for new neural network and memristor design, Nonlinear Dyn., 100 (2020), 3611–3623. https://doi.org/10.1007/s11071-020-05572-z doi: 10.1007/s11071-020-05572-z
    [8] L. L. Huang, G. C. Wu, D. Baleanu, H. Y. Wang, Discrete fractional calculus for interval-valued systems, Fuzzy Sets Syst., 404 (2021), 141–158. https://doi.org/10.1016/j.fss.2020.04.008 doi: 10.1016/j.fss.2020.04.008
    [9] T. Abdeljawad, S. Banerjee, G. C. Wu, Discrete tempered fractional calculus for new chaotic systems with short memory and image encryption, Optik, 2018 (2020), 163698. https://doi.org/10.1016/j.ijleo.2019.163698 doi: 10.1016/j.ijleo.2019.163698
    [10] G. C. Wu, D. Baleanu, Discrete fractional logistic map and its chaos, Nonlinear Dyn., 75 (2014), 283–287. https://doi.org/10.1007/s11071-013-1065-7 doi: 10.1007/s11071-013-1065-7
    [11] R. Dahal, C. S. Goodrich, A monotonocity result for discrete fractional difference operators, Arch. Math., 102 (2014), 293–299. https://doi.org/10.1007/s00013-014-0620-x doi: 10.1007/s00013-014-0620-x
    [12] C. S. Goodrich, A convexity result for fractional differences, Appl. Math. Lett., 35 (2014), 158–162. https://doi.org/10.1016/j.aml.2014.04.013 doi: 10.1016/j.aml.2014.04.013
    [13] F. Atici, M. Uyanik, Analysis of discrete fractional operators, Appl. Anal. Discrete Math., 9 (2015), 139–149. https://doi.org/10.2298/AADM150218007A doi: 10.2298/AADM150218007A
    [14] P. O. Mohammed, O. Almutairi, R. P. Agarwal, Y. S. Hamed, On convexity, monotonicity and positivity analysis for discrete fractional operators defined using exponential kernels, Fractal Fractional, 6 (2022), 55. https://doi.org/10.3390/fractalfract6020055 doi: 10.3390/fractalfract6020055
    [15] T. Abdeljawad, D. Baleanu, Monotonicity analysis of a nabla discrete fractional operator with discrete Mittag-Leffler kernel, Chaos, Solitons Fractals, 102 (2017), 106–110. https://doi.org/10.1016/j.chaos.2017.04.006 doi: 10.1016/j.chaos.2017.04.006
    [16] P. O. Mohammed, C. S. Goodrich, A. B. Brzo, Y. S. Hamed, New classifications of monotonicity investigation for discrete operators with Mittag-Leffler kernel, Math. Biosci. Eng., 19 (2022), 4062–4074. https://doi.org/10.3934/mbe.2022186 doi: 10.3934/mbe.2022186
    [17] C. Goodrich, C. Lizama, Positivity, monotonicity, and convexity for convolution operators, Discrete Contin. Dyn. Syst., 40 (2020), 4961–4983. https://doi.org/10.3934/dcds.2020207 doi: 10.3934/dcds.2020207
    [18] C. S. Goodrich, B. Lyons, Positivity and monotonicity results for triple sequential fractional differences via convolution, Analysis, 40 (2020), 89–103. https://doi.org/10.1515/anly-2019-0050 doi: 10.1515/anly-2019-0050
    [19] C. S. Goodrich, J. M. Jonnalagadda, B. Lyons, Convexity, monotonicity and positivity results for sequential fractional nabla difference operators with discrete exponential kernels, Math. Methods Appl. Sci., 44 (2021), 7099–7120. https://doi.org/10.1002/mma.7247 doi: 10.1002/mma.7247
    [20] P. O. Mohammed, C. S. Goodrich, F. K. Hamasalh, A. Kashuri, Y. S. Hamed, On positivity and monotonicity analysis for discrete fractional operators with discrete Mittag-Leffler kernel, Math. Methods Appl. Sci., (2022), 1–20. https://doi.org/10.1002/mma.8176 doi: 10.1002/mma.8176
    [21] B. Jia, L. Erbe, A. Peterson, Two monotonicity results for nabla and delta fractional differences, Arch. Math., 104 (2015), 589–597. https://doi.org/10.1007/s00013-015-0765-2 doi: 10.1007/s00013-015-0765-2
    [22] R. Dahal, C. S. Goodrich, Mixed order monotonicity results for sequential fractional nabla differences, J. Differ. Equations Appl., 25 (2019), 837–854. https://doi.org/10.1080/10236198.2018.1561883 doi: 10.1080/10236198.2018.1561883
    [23] I. Suwan, T. Abdeljawad, F. Jarad, Monotonicity analysis for nabla h-discrete fractional Atangana-Baleanu differences, Chaos, Solitons Fractals, 117 (2018), 50–59. https://doi.org/10.1016/j.chaos.2018.10.010 doi: 10.1016/j.chaos.2018.10.010
    [24] F. Du, B. Jia, L. Erbe, A. Peterson, Monotonicity and convexity for nabla fractional (q,h)-differences, J. Differ. Equations Appl., 22 (2016), 1224–1243. https://doi.org/10.1080/10236198.2016.1188089 doi: 10.1080/10236198.2016.1188089
    [25] P. O. Mohammed, T. Abdeljawad, F. K. Hamasalh, On Riemann-Liouville and Caputo fractional forward difference monotonicity analysis, Mathematics, 9 (2021), 1303. https://doi.org/10.3390/math9111303 doi: 10.3390/math9111303
    [26] R. Dahal, C. S. Goodrich, B. Lyons, Monotonicity results for sequential fractional differences of mixed orders with negative lower bound, J. Differ. Equations Appl., 27 (2021), 1574–1593. https://doi.org/10.1080/10236198.2021.1999434 doi: 10.1080/10236198.2021.1999434
    [27] C. S. Goodrich, A note on convexity, concavity, and growth conditions in discrete fractional calculus with delta difference, Math. Inequal. Appl., 19 (2016), 769–779. https://doi.org/10.7153/mia-19-57 doi: 10.7153/mia-19-57
    [28] C. S. Goodrich, A sharp convexity result for sequential fractional delta differences, J. Differ. Equations Appl., 23 (2017), 1986–2003. https://doi.org/10.1080/10236198.2017.1380635 doi: 10.1080/10236198.2017.1380635
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1851) PDF downloads(52) Cited by(0)

Figures and Tables

Figures(5)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog