Pulse diagnosis, also known as Nadi Pariksha, is one of the various diagnostic modalities used in Ayurveda. Nadi Pariksha is a way of determining the underlying cause of a sickness that needs extensive knowledge of the Tridosha signals (i.e. Vata, Pitta and Kapha), as well as the peculiarities of each pulse signal and their relationship to each dominant signal. A Nadi expert can gain a sense of the patient's health status by using this approach and then provide treatment based on that information. In the present day, the health monitoring of people has become an essential requirement. A system which keeps track of the patient's health and continuously captures pulse signals will be helpful. In this work a healthcare monitoring system that uses sensors was developed, and the analysis of Vata, Pitta and Kapha for various patients is discussed, as well as the uploading of the same data to a self-made IoT cloud. The mean values of Vata, Pita and Kapha were compared for different age groups; we found that it is more significant for the age group of 41‒50.
Citation: Sanjay Dubey, M. C. Chinnaiah, I. A. Pasha, K. Sai Prasanna, V. Praveen Kumar, R. Abhilash. An IoT based Ayurvedic approach for real time healthcare monitoring[J]. AIMS Electronics and Electrical Engineering, 2022, 6(3): 329-344. doi: 10.3934/electreng.2022020
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Pulse diagnosis, also known as Nadi Pariksha, is one of the various diagnostic modalities used in Ayurveda. Nadi Pariksha is a way of determining the underlying cause of a sickness that needs extensive knowledge of the Tridosha signals (i.e. Vata, Pitta and Kapha), as well as the peculiarities of each pulse signal and their relationship to each dominant signal. A Nadi expert can gain a sense of the patient's health status by using this approach and then provide treatment based on that information. In the present day, the health monitoring of people has become an essential requirement. A system which keeps track of the patient's health and continuously captures pulse signals will be helpful. In this work a healthcare monitoring system that uses sensors was developed, and the analysis of Vata, Pitta and Kapha for various patients is discussed, as well as the uploading of the same data to a self-made IoT cloud. The mean values of Vata, Pita and Kapha were compared for different age groups; we found that it is more significant for the age group of 41‒50.
Fractional difference calculus is a tool used to explain many phenomena in physics, control problems, modeling, chaotic dynamical systems, and various fields of engineering and applied mathematics. In this direction, different kinds of methods and techniques, including numerical and analytical methods, have been utilized by researchers to discuss given fractional discrete and continuous mathematical models and boundary value problems (BVPs) [1,2,3,4]. For some recent developments on the existence, uniqueness, and stability of solutions for fractional differential equations, see, for example, [5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23] and the references therein.
Discrete fractional calculus and difference equations open a new study context for mathematicians. For this reason, they have received increasing attention in recent years. Some real-world processes and phenomena are analyzed with the aid of discrete fractional operators, since such operators provide an accurate tool to describe memory. A large number of research articles dealing with difference equations and discrete fractional boundary value problems (FBVPs) can be found in [24,25,26,27,28,29,30,31,32].
In 2020, Selvam et al. [33] proved the existence of a solution to a discrete fractional difference equation formulated as
{cΔϱξχ(ξ)=Φ(ξ+ϱ−1,χ(ξ+ϱ−1)),1<ϱ≤2,Δχ(ϱ−2)=M1,χ(ϱ+T)=M2, | (1.1) |
for ξ∈[0,T]N0=[0,1,2,…,T], T∈N, η∈[ϱ−1,T+ϱ−1]Nϱ−1, M1 and M2 constants, Φ:[ϱ−2,ϱ+T]Nϱ−2×R⟶R continuous, and where cΔϱξ denotes the ϱth-Caputo difference. Here, motivated by the discrete model (1.1), we shall consider two generalized discrete problems.
Our first goal consists to study existence and uniqueness of solutions to the following discrete fractional equation that involves Caputo discrete derivatives:
{cΔϱξχ(ξ)=Φ(ξ+ϱ−1,χ(ξ+ϱ−1)),2<ϱ≤3,Δχ(ϱ−3)=A1,χ(ϱ+T)=λΔ−βχ(η+β),Δ2χ(ϱ−3)=A2, | (1.2) |
for 0<β≤1, ξ∈[0,T]N0=[0,1,2,…,T], T∈N, η∈[ϱ−1,T+ϱ−1]Nϱ−1, λ, A1 and A2 constants, and where Φ:[ϱ−3,ϱ+T]Nϱ−3×R⟶R is continuous.
The second goal is to study the stability of solutions to the discrete Riemann-Liouville fractional problem
{RLΔϱξχ(ξ)=Φ(ξ+ϱ−1,χ(ξ+ϱ−1)),2<ϱ≤3,Δχ(ϱ−3)=A1,χ(ϱ+T)=λΔ−βχ(η+β),Δ2χ(ϱ−3)=A2, | (1.3) |
for 0<β≤1, ξ∈[0,T]N0=[0,1,2,…,T] and η∈[ϱ−1,T+ϱ−1]Nϱ−1, where RLΔϱξ is the Riemann-Liouville difference operator.
The organization of the paper is as follows. In Section 2, we collect some fundamental definitions available from the literature. In Section 3, we prove the existence and uniqueness results for the discrete FBVP (1.2). Hyers-Ulam and Hyers-Ulam-Rassias stability of the solution for the FBVP (1.3) is established in Section 4. In Section 5, two examples are given to illustrate the obtained results. We end with Section 6 of conclusions.
We begin by recalling some necessary definitions and essential lemmas that will be used throughout the paper.
Definition 2.1. (See [27]) Let ϱ>0. The ϱ-order fractional sum of Φ is defined by
Δ−ϱξΦ(ξ)=1Γ(ϱ)ξ−ϱ∑l=a(ξ−l−1)(ϱ−1)Φ(l), | (2.1) |
where ξ∈Na+ϱ:={a+ϱ,a+ϱ+1,…} and ξ(ϱ):=Γ(ξ+1)Γ(ξ+1−ϱ).
Definition 2.2. (See [27]) Let ϱ>0 and Φ be defined on Na. The ϱ-order Caputo fractional difference of Φ is defined by
CaΔϱξΦ(ξ)=Δ−(n−ϱ)(ΔnΦ(ξ))=1Γ(n−ϱ)ξ−(n−ϱ)∑l=a(ξ−l−1)(n−ϱ−1)ΔnΦ(l), | (2.2) |
while the Riemann-Liouville fractional difference of Φ is defined by
RLaΔϱξΦ(ξ)=ΔnΔ−(n−ϱ)Φ(ξ), | (2.3) |
where ξ∈Na+n−ϱ and n−1<ϱ≤n.
Lemma 2.1. (See [24,27]) For ϱ>0,
Δ−ϱCaΔϱξΦ(ξ)=Φ(ξ)+C0+C1ξ+⋯+CN−1ξ(N−1), | (2.4) |
where Ci∈R, i=1,2,…,N−1, Φ is defined on Na, and 0≤N−1<ϱ≤N.
Lemma 2.2. (See ([32]) Let 0≤N−1<ϱ≤N and Φ be defined on Na. Then,
Δ−ϱRL0ΔϱξΦ(ξ)=Φ(ξ)+B1ξϱ−1+B2ξ(ϱ−2)+⋯+BNξ(ϱ−N), | (2.5) |
for B1,…,BN∈R.
Lemma 2.3. (See [31]) Let ϱ and ξ be any arbitrary real numbers. Then,
(1)ξ−ϱ∑l=0(ξ−l−1)(ϱ−1)=Γ(ξ+1)ϱΓ(ξ−ϱ+1),(2)L∑l=0(ξ−L−l−1)(ϱ−1)=Γ(ϱ+L+1)ϱΓ(L+1). |
Lemma 2.4. (See [31]) For ζ∈R∖(Z−∖{0}), we have
Δ−ϱξ(ζ)=Γ(ζ+1)Γ(ζ+ϱ+1)ξ(ζ+ϱ). |
In this section, we prove the existence and uniqueness of solution for the Caputo three-point discrete fractional problem (1.2). To accomplish this, we denote by C(Nϱ−3,ϱ+T,R) the collection of all continuous functions χ with the norm
‖χ‖=max{|χ(ξ)|:ξ∈Nϱ−3,ϱ+T}. |
Lemma 3.1. Let 2<ϱ≤3 and Φ:[ϱ−3,ϱ+T]Nϱ−3⟶R. A function χ(ξ) (ξ∈[ϱ−3,ϱ+T]Nϱ−3) that satisfies the discrete FBVP
{cΔϱξχ(ξ)=Φ(ξ+ϱ−1),2<ϱ≤3,Δχ(ϱ−3)=A1,χ(ϱ+T)=λΔ−βχ(η+β),Δ2χ(ϱ−3)=A2,0<β≤1, | (3.1) |
is given by
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)−λK1Γ(ϱ)η∑l=ϱl−ϱ∑ξ=0(η+β−ρ(l))(β−1)(l−ρ(ξ))(ϱ−1)Φ(ξ+ϱ−1)+Γ(β)K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1)+K2+[A1−A2(ϱ−3)]ξ(1)+A22ξ(2), | (3.2) |
with
K1=λη∑l=ϱ−3(η+β−ρ(l))(β−1)−Γ(β), | (3.3) |
and
K2=λK1[A2(ϱ−3)−A1]η∑l=ϱ−3(η+β−ρ(l))(β−1)l(1)−A22K1λη∑l=ϱ−3(η+β−ρ(l))(β−1)l(2)+Γ(β)K1(ϱ+T)[A1−A2(ϱ−3)+A22(ϱ+T−1)]. | (3.4) |
Proof. Let χ(ξ) be a solution to (3.1). Applying Lemma 2.1 and Definition 2.1, we find that
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+C0+C1ξ(1)+C2ξ(2), | (3.5) |
for ξ∈[ϱ−3,ϱ+T]Nϱ−3, where C0,C1,C2∈R. By using the difference of order 1 for (3.5), we have
Δχ(ξ)=1Γ(ϱ−1)ξ−ϱ+1∑l=0(ξ−ρ(l))(ϱ−2)Φ(l+ϱ−1)+C1+2C2ξ(1), |
and
Δ2χ(ξ)=1Γ(ϱ−2)ξ−ϱ+2∑l=0(ξ−ρ(l))(ϱ−3)Φ(l+ϱ−1)+2C2. |
Now, from conditions Δχ(ϱ−3)=A1 and Δ2χ(ϱ−3)=A2, we obtain that
C1=A1−A2(ϱ−3),C2=A22. |
Therefore,
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+C0+[A1−A2(ϱ−3)]ξ(1)+A22ξ(2), | (3.6) |
for ξ∈[ϱ−3,ϱ+T]Nϱ−3. By using formula (3.5), one has
Δ−βχ(ξ)=C1Γ(β)ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)l(1)+C2Γ(β)ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)l(2)+C0Γ(β)ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)+1Γ(ϱ)Γ(β)ξ−β∑l=ϱl−ϱ∑ξ=0(ξ−ρ(l))(β−1)(l−ρ(ξ))(ϱ−1)Φ(ξ+ϱ−1). | (3.7) |
The other condition of (3.1) gives
λΔ−βχ(η+β)=λ[A1−A2(ϱ−3)]Γ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(1) +λA22Γ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(2)+λC0Γ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1) +λΓ(ϱ)Γ(β)η∑l=ϱl−ϱ∑ξ=0(η+β−ρ(l))(β−1)(l−ρ(ξ))(ϱ−1)Φ(ξ+ϱ−1)=1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1)+C0 +[A1−A2(ϱ−3)](ϱ+T)(1)+A22(ϱ+T)(2). |
We have
C0=Γ(β)K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1)+K2−λK1Γ(ϱ)η∑l=ϱl−ϱ∑ξ=0(η+β−ρ(l))(β−1)(l−ρ(ξ))(ϱ−1)Φ(ξ+ϱ−1), |
where K1 and K2 are defined by (3.3) and (3.4), and one obtains (3.2) by substituting the value of C0 into (3.6).
Now, let us consider the operator H:C(Nϱ−3,ϱ+T,R)→C(Nϱ−3,ϱ+T,R) defined by
(Hχ)(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))−λK1Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))+Γ(β)K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))+K2+[A1−A2(ϱ−3)]ξ(1)+A22ξ(2). |
Theorem 3.1. Assume that:
(H1) Function Φ satisfies |Φ(ξ,χ1)−Φ(ξ,χ2)|≤K|χ1−χ2|, where K>0, ∀ξ∈Nϱ−3,ϱ+T and χ1,χ2∈C(Nϱ−3,ϱ+T,R). The discrete FBVP (3.1) has a unique solution on C(Nϱ−3,ϱ+T,R) provided
Γ(ϱ+T+1)Γ(ϱ+1)Γ(T+1)(1+Γ(β)K1)+MλK1Γ(ϱ)≤1K | (3.8) |
with
M=|η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)|. | (3.9) |
Proof. Let χ1,χ2∈C(Nϱ−3,ϱ+T,R). Then, for each ξ∈Nϱ−3,ϱ+T, we have
|(Hχ1)(ξ)−(Hχ2)(ξ)|≤1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)×|Φ(l+ϱ−1,χ1(l+ϱ−1))−Φ(l+ϱ−1,χ2(l+ϱ−1))|+λK1Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)×|Φ(l+ϱ−1,χ1(l+ϱ−1))−Φ(l+ϱ−1,χ2(l+ϱ−1))|+Γ(β)K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)×|Φ(l+ϱ−1,χ1(l+ϱ−1))−Φ(l+ϱ−1,χ2(l+ϱ−1))|. |
It follows that
‖(Hχ1)(ξ)−(Hχ2)(ξ)‖≤K‖χ1−χ2‖Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)+λK‖χ1−χ2‖K1Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)+Γ(β)K‖χ1−χ2‖K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)≤K‖χ1−χ2‖Γ(ϱ)Γ(ϱ+T+1)ϱΓ(T+1)+λK‖χ1−χ2‖K1Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)+Γ(β)K‖χ1−χ2‖K1Γ(ϱ)Γ(ϱ+T+1)ϱΓ(T+1)≤K‖χ1−χ2‖[Γ(ϱ+T+1)Γ(ϱ+1)Γ(T+1)+MλK1Γ(ϱ)+Γ(β)Γ(ϱ+T+1)K1Γ(ϱ+1)Γ(T+1)]. |
From (3.8), we conclude that H is a contraction. Then, by the Banach contraction principle, the discrete problem (3.1) has a unique solution on C(Nϱ−3,ϱ+T,R).
Theorem 3.2. Suppose that Φ:[ϱ−3,ϱ+T]Nϱ−3×R⟶R is a continuous function and
R=max{|Φ(l+ϱ−1,χ(l+ϱ−1))|,ξ∈Nϱ−3,ϱ+T,χ∈C(Nϱ−3,ϱ+T,R);‖χ‖≤2|K2|}. |
The discrete problem (3.1) has a solution provided that
R≤|K2|−|[A1−A2(ϱ−3)]|(ϱ+T)(1)−|A22|(ϱ+T)(2)Γ(ϱ+T+1)Γ(ϱ+1)Γ(T+1)(1+Γ(β)|K1|)+M|λ|Γ(ϱ)|K1|. | (3.10) |
Proof. Let G={χ∈C(Nϱ−3,ϱ+T,R);‖χ‖≤2|K2|}. For χ(ξ)∈G, we get
|(Hχ)(ξ)|=|1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))+λK1Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))−Γ(β)K1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))+K2+[A1−A2(ϱ−3)]ξ(1)+A22ξ(2)|≤1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)|Φ(l+ϱ−1,χ(l+ϱ−1))|+|λ||K1|Γ(ϱ)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)|Φ(l+ϱ−1,χ(l+ϱ−1))|+Γ(β)|K1|Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)|Φ(l+ϱ−1,χ(l+ϱ−1))|+|K2|+|[A1−A2(ϱ−3)]ξ(1)|+|A22ξ(2)|≤RΓ(ϱ)[ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)+|λ||K1|η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)+Γ(β)|K1|T∑l=0(ϱ+T−ρ(l))(ϱ−1)]+|K2|+|[A1−A2(ϱ−3)]|(ϱ+T)(1)+|A22|(ϱ+T)(2)≤RΓ(ϱ)[Γ(ϱ+T+1)ϱΓ(T+1)(1+Γ(β)|K1|)+M|λ||K1|]+|K2|+|[A1−A2(ϱ−3)]|(ϱ+T)(1)+|A22|(ϱ+T)(2). |
From (3.10), we have ‖Hχ‖≤2|K2|, which implies that H:G→G. By Brouwer's fixed point theorem, we know that the discrete problem (3.1) has a solution.
In this section, we study the Hyers-Ulam and Hyers-Ulam-Rassias stability for the solutions of the discrete Riemann-Liouville (RL) FBVP
{RLΔϱξχ(ξ)=Φ(ξ+ϱ−1,χ(ξ+ϱ−1)),2<ϱ≤3,Δχ(ϱ−3)=A1,χ(ϱ+T)=λΔ−βχ(η+β),Δ2χ(ϱ−3)=A2,0<β≤1, | (4.1) |
for ξ∈[0,1,2,…,T]=[0,T]N0 and η∈[ϱ−1,T+ϱ−1]Nϱ−1, where RLΔϱξ is the RL fractional difference operator. We begin by proving the following lemma.
Lemma 4.1. Suppose that 2<ϱ≤3 and Φ:[ϱ−3,ϱ+T]Nϱ−3⟶R. A function χ satisfies the discrete problem
{RLΔϱξχ(ξ)=Φ(ξ+ϱ−1),2<ϱ≤3,Δχ(ϱ−3)=A1,χ(ϱ+T)=λΔ−βχ(η+β),Δ2χ(ϱ−3)=A2,0<β≤1, | (4.2) |
if, and only if, χ(ξ), ξ∈[ϱ−3,ϱ+T]Nϱ−3, has the form
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+{[A2−A1(ϱ−3)]Γ(ϱ)+fΦ+dϱhϱ(ϱ−3)2(ϱ−1)}ξ(ϱ−1)+[A1−1hϱ[fΦ+dϱ](ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)ξ(ϱ−2)+fΦ+dϱhϱξ(ϱ−3), | (4.3) |
where
hϱ=ϱ−3ϱ−2(ϱ+T)(ϱ−2)−ϱ−32(ϱ−1)(ϱ+T)(ϱ−1)−(ϱ+T)(ϱ−3) | (4.4) |
+λ(ϱ−3)Γ(β)2(ϱ−1)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−1)−λ(ϱ−3)Γ(β)(ϱ−2)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−2)+λΓ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−3),dϱ=A1(ϱ+T)(ϱ−2)Γ(ϱ−1)−[A2−A1(ϱ−3)]λΓ(ϱ)Γ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−1) | (4.5) |
−A1λΓ(ϱ−1)Γ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−2)+[A2−A1(ϱ−3)]Γ(ϱ)(ϱ+T)(ϱ−1),fΦ=−λΓ(ϱ)Γ(β)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(τ+ϱ−1) | (4.6) |
+1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1). |
Proof. Let χ(ξ) be a solution to (4.2). Applying Lemma 2.2 and Definition 2.1, we obtain that the general solution of (4.2) is given by
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+B1ξ(ϱ−1)+B2ξ(ϱ−2)+B3ξ(ϱ−3), | (4.7) |
ξ∈[ϱ−3,ϱ+T]Nϱ−3, where B1,B2,B3∈R. The first order difference of (4.7) is
Δχ(ξ)=1Γ(ϱ−1)ξ−ϱ+1∑l=0(ξ−ρ(l))(ϱ−2)Φ(l+ϱ−1)+B1(ϱ−1)ξ(ϱ−2)+B2(ϱ−2)ξ(ϱ−3)+B3(ϱ−3)ξ(ϱ−4), |
while
Δ2χ(ξ)=1Γ(ϱ−2)ξ−ϱ+2∑l=0(ξ−ρ(l))(ϱ−3)Φ(l+ϱ−1)+B1(ϱ−1)(ϱ−2)ξ(ϱ−3)+B2(ϱ−2)(ϱ−3)ξ(ϱ−4)+B3(ϱ−3)(ϱ−4)ξ(ϱ−5). |
From the conditions Δχ(ϱ−3)=A1 and Δ2χ(ϱ−3)=A2, we obtain that
B2=1Γ(ϱ−1)[A1−B3(ϱ−3)Γ(ϱ−2)], |
and
B1=1Γ(ϱ)[A2−A1(ϱ−3)]+B3(ϱ−3)2(ϱ−1). |
Now, by using the difference of order β for (4.7), it follows that
Δ−βχ(ξ)=1Γ(β){1Γ(ϱ)[A2−A1(ϱ−3)]+B3(ϱ−3)2(ϱ−1)}ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)l(ϱ−1)+B3Γ(β)ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)l(ϱ−3)+[A1−B3(ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)Γ(β)ξ−β∑l=ϱ−3(ξ−ρ(l))(β−1)l(ϱ−2)+1Γ(ϱ)Γ(β)ξ−β∑l=ϱl−ϱ∑τ=0(ξ−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(τ+ϱ−1). | (4.8) |
Based on condition (4.1), we have
λΔ−βχ(η+β)=λΓ(β){1Γ(ϱ)[A2−A1(ϱ−3)]+B3(ϱ−3)2(ϱ−1)}η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−1)+λΓ(ϱ−1)Γ(β)[A1−B3(ϱ−3)Γ(ϱ−2)]η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−2)+B3λΓ(β)η∑l=ϱ−3(η+β−ρ(l))(β−1)l(ϱ−3)+λΓ(ϱ)Γ(β)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(τ+ϱ−1)=1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1)+1Γ(ϱ−1)[A1−B3(ϱ−3)Γ(ϱ−2)](ϱ+T)(ϱ−2)+{1Γ(ϱ)[A2−A1(ϱ−3)]+B3(ϱ−3)2(ϱ−1)}(ϱ+T)(ϱ−1)+B3(ϱ+T)(ϱ−3). |
Then,
B3=1hϱ[fΦ+dϱ],B2=1Γ(ϱ−1)[A1−1hϱ[fΦ+dϱ](ϱ−3)Γ(ϱ−2)],B1=1Γ(ϱ)[A2−A1(ϱ−3)]+1hϱ[fΦ+dϱ](ϱ−3)2(ϱ−1), |
where hϱ, dϱ and fΦ are defined by (4.4)-(4.6), respectively. Substituting the values of the constants B1, B2 and B3 into (4.7), we obtain (4.3) and our proof is complete.
From Lemma 4.1, the solution of the discrete RL problem (4.1) is given by the formula
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1))+{[A2−A1(ϱ−3)]Γ(ϱ)+fχ+dϱhϱ(ϱ−3)2(ϱ−1)}ξ(ϱ−1)+[A1−1hϱ[fΦ+dϱ](ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)ξ(ϱ−2)+fχ+dϱhϱξ(ϱ−3), | (4.9) |
where dρ and hρ are defined by (4.4) and (4.5), respectively, and
fχ=−λΓ(ϱ)Γ(β)η∑l=ϱl−ϱ∑τ=0(η+β−ρ(l))(β−1)(l−ρ(τ))(ϱ−1)Φ(τ+ϱ−1,χ(τ+ϱ−1))+1Γ(ϱ)T∑l=0(ϱ+T−ρ(l))(ϱ−1)Φ(l+ϱ−1,χ(l+ϱ−1)). | (4.10) |
Lemma 4.2. If χ is a solution of (4.3), then
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+Q(ξ)+fχK(ξ), | (4.11) |
where
Q(ξ)={[A2−A1(ϱ−3)]Γ(ϱ)+dϱ(ϱ−3)2hϱ(ϱ−1)}ξ(ϱ−1)+[A1−dϱhϱ(ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)ξ(ϱ−2)+dϱhϱξ(ϱ−3), |
and
K(ξ)=(ϱ−3)2hϱ(ϱ−1)ξ(ϱ−1)−(ϱ−3)hϱ(ϱ−2)ξ(ϱ−2)+ξ(ϱ−3)hϱ. |
Proof. Take χ as a solution of (4.2). For ξ∈[ϱ−3,ϱ+T]Nϱ−3, then
χ(ξ)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+{[A2−A1(ϱ−3)]Γ(ϱ)+fχ+dϱhϱ(ϱ−3)2(ϱ−1)}ξ(ϱ−1)+[A1−1hϱ[fχ+dϱ](ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)ξ(ϱ−2)+fχ+dϱhϱξ(ϱ−3)=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+{[A2−A1(ϱ−3)]Γ(ϱ)+dϱ(ϱ−3)2hϱ(ϱ−1)}ξ(ϱ−1)+[A1−dϱhϱ(ϱ−3)Γ(ϱ−2)]Γ(ϱ−1)ξ(ϱ−2)+dϱhϱξ(ϱ−3)+fχ[(ϱ−3)2hϱ(ϱ−1)ξ(ϱ−1)−(ϱ−3)hϱ(ϱ−2)ξ(ϱ−2)+ξ(ϱ−1)hϱ]=1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1)+Q(ξ)+fχK(ξ). |
The proof is complete.
Definition 4.1. We say that the discrete RL problem (4.1) is Hyers-Ulam stable if for each function ν∈C(Nϱ−3,ϱ+T,R) of
|RLΔϱξν(ξ)−Φ(ξ+ϱ−1,ν(ξ+ϱ−1))|≤ϵ,ξ∈[0,T]N0, | (4.12) |
and ϵ>0, there exists χ∈C(Nϱ−3,ϱ+T,R) solution of (4.1) and δ>0 such that
|ν(ξ)−χ(ξ)|≤δϵ,ξ∈[ϱ−3,ϱ+T]Nϱ−3. | (4.13) |
Definition 4.2. We say that the discrete RL problem (4.1) is Hyers-Ulam–Rassias stable if for each function ν∈C(Nϱ−3,ϱ+T,R) of
|RLΔϱξν(ξ)−Φ(ξ+ϱ−1,ν(ξ+ϱ−1))|≤ϵθ(ξ+ϱ−1),ξ∈[0,T]N0, | (4.14) |
and ϵ>0, there exists χ∈C(Nϱ−3,ϱ+T,R) solution of (4.1) and δ2>0 such that
|ν(ξ)−χ(ξ)|≤δ2ϵθ(ξ+ϱ−1),ξ∈[ϱ−3,ϱ+T]Nϱ−3. | (4.15) |
Remark 4.1. A function χ(ξ)∈C(Nϱ−3,ϱ+T,R) is a solution of (4.12) if, and only if, there exists μ:[ϱ−3,ϱ+T]Nϱ−3⟶R satisfying:
(H2) |μ(ξ+ϱ−1)|≤ϵ,ξ∈[0,T]N0;
(H3) RLΔϱξν(ξ)=Φ(ξ+ϱ−1,ν(ξ+ϱ−1))+μ(ξ+ϱ−1),ξ∈[0,T]N0.
Remark 4.2. A function χ(ξ)∈C(Nϱ−3,ϱ+T,R) is a solution of (4.14) if, and only if, there exists μ:[ϱ−3,ϱ+T]Nϱ−3⟶R satisfying
(H4) |μ(ξ+ϱ−1)|≤ϵθ(ξ+ϱ−1),ξ∈[0,T]N0,
(H5) RLΔϱξν(ξ)=Φ(ξ+ϱ−1,ν(ξ+ϱ−1))+μ(ξ+ϱ−1),ξ∈[0,T]N0.
Lemma 4.3. If ν satisfies (4.12), then
|ν(ξ)−1Γ(ϱ)ξ−ϱ∑l=0(ξ−ρ(l))(ϱ−1)Φ(l+ϱ−1,ν(l+ϱ−1))−Q(ξ)−fνK(ξ)|≤ϵΓ(ϱ+T+1)Γ(ϱ+1)Γ(T+1). |
Proof. Using our hypothesis, and based on Remark 4.1, the solution to (\mathcal{H}3) satisfies
\begin{align*} \nu(\xi)& = \dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi -\rho(l))^{(\varrho-1)}\Phi(l+\varrho-1,\nu(l+\varrho-1)) +Q(\xi)+f_{\nu}K(\xi)\\ &\quad +\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi -\varrho}(\xi-\rho(l))^{(\varrho-1)}\mu(l+\varrho-1). \end{align*} |
Hence,
\begin{align*} \bigg|\nu(\xi) &-\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)} \Phi(l+\varrho-1,\nu(l+\varrho-1))-Q(\xi)-f_{\nu}K(\xi)\bigg|\\ & = \bigg|\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi -\varrho}(\xi-\rho(l))^{(\varrho-1)}\mu(l+\varrho-1)\bigg|\\ &\leq\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi -\varrho}(\xi-\rho(l))^{(\varrho-1)}|\mu(l+\varrho-1)|\\ &\leq\dfrac{\epsilon\Gamma(\varrho+T+1)}{\Gamma(\varrho+1)\Gamma(T+1)}, \end{align*} |
and the desired inequality is derived.
Theorem 4.1. If condition (\mathcal{H}1) holds and (4.13) is satisfied, then the discrete RL problem (4.1) is Hyers-Ulam stable under the condition
\begin{equation} K\leq\dfrac{\Gamma(\beta)\Gamma(T+1)\Gamma(\varrho+1)}{2M_{1} \Gamma(\varrho+T+1)\Gamma(\beta)+ M M_{1}\lambda\varrho\Gamma(T+1)}, \end{equation} | (4.16) |
where M_{1} = \max(1, |K(\xi)|) .
Proof. Let \xi\in[\varrho-3, \varrho+T]_{\mathbb{N}_{\varrho-3}} . From Lemma 8, we have
\begin{align*} |\nu(\xi)-\chi(\xi)| &\leq\bigg|\nu(\xi)-\dfrac{1}{\Gamma(\varrho)} \sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)}\Phi(l+\varrho-1, \chi(l+\varrho-1))-Q(\xi)-f_{\chi}K(\xi)\bigg|\\ &\leq\bigg|\nu(\xi)-\dfrac{1}{\Gamma(\varrho)} \sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)} \Phi(l+\varrho-1,\nu(l+\varrho-1))-Q(\xi)-f_{\nu}K(\xi)\bigg|\\ &\quad +\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)}| \Phi(l+\varrho-1,\chi(l+\varrho-1))-\Phi(l+\varrho-1,\nu(l+\varrho-1))|\\ &\quad +|K(\xi)||f_{\nu}-f_{\chi}|. \end{align*} |
It follows that
\begin{align*} |\nu(\xi)-\chi(\xi)| &\leq\dfrac{\epsilon\Gamma(\varrho+T+1)}{\Gamma(\varrho+1)\Gamma(T+1)} +\dfrac{K}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)}| \chi(l+\varrho-1)-\nu(l+\varrho-1)|\\ &\quad +|K(\xi)|K\bigg\lbrace\dfrac{\lambda}{\Gamma(\varrho)\Gamma(\beta)} \sum\limits_{l = \varrho}^{\eta}\sum\limits_{\tau = 0}^{l-\varrho}(\eta +\beta-\rho(l))^{(\beta-1)}(l-\rho(\tau))^{(\varrho-1)}|\nu(l+\varrho-1) -\chi(l+\varrho-1)|\\ &\quad +\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{T}(\varrho+T-\rho(l))^{(\varrho-1)}| \chi(l+\varrho-1)-\nu(l+\varrho-1)|\bigg\rbrace\\ &\leq\dfrac{\epsilon\Gamma(\varrho+T+1)}{\Gamma(\varrho+1)\Gamma(T+1)} +\dfrac{K\Vert\chi-\nu\Vert}{\Gamma(\varrho)}\dfrac{\Gamma(\xi+1)}{\varrho \Gamma(\xi+1-\varrho)}\\ &\quad +|K(\xi)|K\Vert\chi-\nu\Vert\bigg[\dfrac{M\lambda}{\Gamma(\varrho)\Gamma(\beta)} +\dfrac{1}{\Gamma(\varrho)}\dfrac{\Gamma(\varrho+T+1)}{\varrho\Gamma(T+1)}\bigg]\\ &\leq\dfrac{\epsilon\Gamma(\varrho+T+1)}{\Gamma(\varrho+1)\Gamma(T+1)} +\dfrac{2K M_{1}}{\Gamma(\varrho+1)}\dfrac{\Gamma(\varrho+T+1)}{ \Gamma(T+1)}\Vert\chi-\nu\Vert +\Vert\chi-\nu\Vert \dfrac{K M M_{1}\lambda}{\Gamma(\varrho)\Gamma(\beta)}. \end{align*} |
Therefore,
\begin{equation*} \Vert\nu-\chi\Vert\leq\dfrac{\epsilon\Gamma(\varrho+T+1)}{\Gamma(\varrho+1) \Gamma(T+1)}+\Vert\nu-\chi\Vert\bigg[\dfrac{2K M_{1}}{\Gamma(\varrho+1)} \dfrac{\Gamma(\varrho+T+1)}{\Gamma(T+1)} +\dfrac{K M M_{1}\lambda}{\Gamma(\varrho)\Gamma(\beta)}\bigg]. \end{equation*} |
Moreover, \Vert\nu-\chi\Vert\leq\epsilon\delta , where
\delta = \dfrac{\Gamma(\beta)\Gamma(\varrho+T+1)}{\Gamma(\beta) \Gamma(T+1)\Gamma(\varrho+1)-2K M_{1}\Gamma(\varrho+T+1)\Gamma(\beta) -K M M_{1}\lambda\varrho\Gamma(T+1)} > 0. |
Thus, the discrete RL problem (4.1) is Hyers-Ulam stable.
Lemma 4.4. If v solves (4.14) under the condition:
(\mathcal{H}6) The function \theta:[\varrho-3, \varrho+T]_{\mathbb{N}_{\varrho-3}} \longrightarrow\mathbb{R} is increasing and there exists a constant \gamma > 0 such that
\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi -\rho(l))^{(\varrho-1)}\theta(l+\varrho-1) \leq\gamma\theta(\xi+\varrho-1),\quad \xi\in[0,T]_{\mathbb{N}_{0}}, |
then
\begin{equation*} \bigg|\nu(\xi)-\dfrac{1}{\Gamma(\varrho)} \sum\limits_{l = 0}^{\xi-\varrho}(\xi-\rho(l))^{(\varrho-1)} \Phi(l+\varrho-1,\nu(l+\varrho-1))-Q(\xi)-f_{\phi_{\nu}}K(\xi)\bigg| \leq\gamma\theta(\xi+\varrho-1). \end{equation*} |
Proof. Let \nu satisfy (4.14). From Remark 4.2, the solution to (\mathcal{H}5) satisfies
\begin{align*} \nu(\xi) & = \dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho}(\xi -\rho(l))^{(\varrho-1)}\Phi(l+\varrho-1,\nu(l+\varrho-1))+Q(\xi)+f_{\nu}K(\xi)\\ &+\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi -\varrho}(\xi-\rho(l))^{(\varrho-1)}\mu(l+\varrho-1). \end{align*} |
Hence,
\begin{align*} \bigg|\nu(\xi) &-\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho} (\xi-\rho(l))^{(\varrho-1)}\Phi(l+\varrho-1,\nu(l+\varrho-1))-Q(\xi)-f_{\nu}K(\xi)\bigg|\\ & = \bigg|\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho} (\xi-\rho(l))^{(\varrho-1)}\mu(l+\varrho-1)\bigg|\\ &\leq\dfrac{1}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho} (\xi-\rho(l))^{(\varrho-1)}|\mu(l+\varrho-1)|\\ &\leq\dfrac{\epsilon}{\Gamma(\varrho)}\sum\limits_{l = 0}^{\xi-\varrho} (\xi-\rho(l))^{(\varrho-1)}|\theta(l+\varrho-1)|\\ &\leq\gamma\epsilon\theta(l+\varrho-1), \end{align*} |
and the desired inequality is derived.
Remark 4.3. About the restrictiveness of hypotheses (\mathcal{H}1) – (\mathcal{H}6) , and the bounds imposed on the family of discrete systems that satisfy them, one should note that such hypotheses are the usual conditions for proving existence, uniqueness or stability of solutions. In fact, the conditions (\mathcal{H}2) – (\mathcal{H}6) are considered as the fundamental conditions in the definition of Hyers-Ulam-Rassias stability. Condition (\mathcal{H}1) is a standard Lipschitz condition while other constants are computed based on the given fractional system. Therefore, these conditions are natural and, in real systems, with specified numerical data, their expressions are reduced to numerical bounds.
Theorem 4.2. If the inequality (4.16) and the hypotheses (\mathcal{H}1) and (\mathcal{H}6) are satisfied, then the discrete RL problem (4.1) is Hyers-Ulam-Rassias stable.
Proof. From Lemmas 4.4 and 2.3, we obtain that
\Vert\nu-\chi\Vert\leq\delta_{2}\epsilon\theta(\xi+\varrho-1), |
where
\delta_2 = \dfrac{\Gamma(\varrho+1)\Gamma(\beta) \Gamma(T+1)}{\Gamma(\varrho+1)\Gamma(\beta)\Gamma(T+1) -2K M_{1}\Gamma(\beta)\Gamma(\varrho+T+1) -K M M_{1}\lambda\varrho\Gamma(T+1)} > 0. |
Thus, the discrete RL problem (4.1) is Hyers-Ulam-Rassias stable.
In this section, we consider two examples to illustrate the obtained results.
Example 5.1. Let
\begin{equation} \begin{cases} ^{*}\Delta_{\xi}^{\varrho}\chi(\xi) = \Phi(\xi+\varrho-1,\chi(\xi+\varrho-1)), \quad \xi\in {\mathbb{N}_{0,4}},\\[0.3cm] \Delta\chi(\varrho-3) = 1, \quad \chi(\varrho+4) = 0.3\Delta^{-0.5}\chi(\eta+0.5), \quad \Delta^{2}\chi(\varrho-3) = 0, \end{cases} \end{equation} | (5.1) |
where ^{*}\Delta_{\xi}^{\varrho} denotes the operator ^{c}\Delta_{\xi}^{\varrho} or ^{RL}\Delta_{\xi}^{\varrho} . Set \beta = 0.5 , T = 4 , \lambda = 0.7 , A_1 = 1 , A_2 = 0 , and
\Phi(\xi+1.5,\chi(\xi+1.5)) = \dfrac{137}{10^5}\sin(\chi(\xi+1.5)). |
\bullet If ^{*}\Delta_{\xi}^{\varrho}\chi(\xi) = {^{c}\Delta}_{\xi}^{\frac{5}{2}}\chi(\xi) and \eta = \frac{5}{2} , then we obtain that
\begin{align*} K_{1}& = \lambda\sum\limits_{l = \varrho-3}^{\eta}(\eta+\beta-\rho(l))^{(\beta-1)}-\Gamma(\beta)\\ & = \dfrac{\lambda\Gamma(\eta+\beta-\varrho+4)}{\beta \Gamma(\eta-\varrho+4)}-\Gamma(\beta)\\ & = 0.9416, \end{align*} |
\begin{equation} M = \bigg|\sum\limits_{l = \varrho}^{\eta}\sum\limits_{\xi = 0}^{l-\varrho}(\eta +\beta-\rho(l))^{(\beta-1)}(l-\rho(\xi))^{(\varrho-1)}\bigg| = 2.3562. \end{equation} | (5.2) |
Hence, the inequality (3.8) takes the form
\dfrac{\Gamma(\varrho+T+1)}{\Gamma(\varrho+1)\Gamma(T+1)}\bigg(1 +\dfrac{\Gamma(\beta)}{K_{1}}\bigg)+\dfrac{M\lambda}{K_{1} \Gamma(\varrho)}\approx 68.9403\leq\dfrac{1}{K} \approx 729.9270, |
such that
\begin{equation*} K = \dfrac{137}{10^5}. \end{equation*} |
From Theorem 3.1, the discrete problem (5.1) has a unique solution.
\bullet In the case ^{*}\Delta_{\xi}^{\varrho}\chi(\xi) = {^{RL}\Delta}_{\xi}^{3}\chi(\xi) and \eta = 3 , we obtain
\begin{align*} M& = 3.5449,\\ M&_1 = 1.8824,\\ h_{\varrho} & = \dfrac{\lambda\Gamma(\eta+\beta-\varrho+4)}{\Gamma(\beta+1) \Gamma(\eta-\varrho+4)}-1 = 0.5313,\\ K_{1}& = \dfrac{\lambda\Gamma(\eta+\beta-\varrho+4)}{\beta \Gamma(\eta-\varrho+4)}-\Gamma(\beta) = 0.9416. \end{align*} |
Also,
\begin{equation} \dfrac{\Gamma(\beta)\Gamma(T+1)\Gamma(\varrho+1)}{2M_{1} \Gamma(\varrho+T+1)\Gamma(\beta)+ M M_{1}\lambda\varrho\Gamma(T+1)} \approx 0.0075. \end{equation} | (5.3) |
If K = 0.0014 < 0.0075 and
\begin{align} \vert^{RL}\Delta_{\xi}^{3}\nu(\xi)-\Phi(\xi+2,v(\xi+2))\vert \leq\epsilon, \,\,\,\,\xi\in[0,4]_{\mathbb{N}_0}, \end{align} | (5.4) |
holds, then, by Theorem 4.1, the discrete RL problem (5.1) is Hyers-Ulam stable.
Example 5.2. Let
\begin{equation} \begin{cases} ^{c}\Delta_{\xi}^{2.4}\chi(\xi) = \dfrac{1}{10^7}\chi^{4}(\xi+1.4), \quad \xi\in {\mathbb{N}_{0,2}},\\[0.3cm] \Delta\chi(-0.4) = 2, \quad \chi(3.4) = 0.8\Delta^{-1/3}\chi(1/3+2.4), \quad \Delta^{2}\chi(-0.6) = 0. \end{cases} \end{equation} | (5.5) |
After some calculations, we find that
\begin{align*} M& = 3.277,\\ K_{1}& = \lambda\sum\limits_{l = \varrho-3}^{\eta}(\eta +\beta-\rho(l))^{(\beta-1)}-\Gamma(\beta) = 1.0253,\\ K_{2}& = \dfrac{A_{1}\Gamma(\beta)}{K_{1}}(\varrho+T) -\dfrac{\lambda A_{1}}{K_{1}}\frac{(\eta-\beta(3-\varrho)) \Gamma(\eta-\varrho+\beta+4)}{\beta(\beta+1)\Gamma(\eta-\varrho+4)} = 16.2963. \end{align*} |
We define the following Banach space:
C(\mathbb{N}_{\varrho-3,\varrho+T},\mathbb{R}) = \left\{\chi(t)|[-0.5,6.5]_{\mathbb{N}_{-0.5}} \to\mathbb{R}, \,\,\Vert\chi\Vert\leq2|K_{2}| = 32.5927\right\}. |
Note that
\begin{equation*} \dfrac{|K_{2}|-\big|[A_{1}-A_{2}(\varrho-3)]\big|(\varrho+T)^{(1)} -\left|\dfrac{A_{2}}{2}\right|(\varrho+T)^{(2)}}{\dfrac{\Gamma(\varrho+T+1)}{ \Gamma(\varrho+1)\Gamma(T+1)}\left(1+\dfrac{\Gamma(\beta)}{|K_{1}|}\right) +\dfrac{M|\lambda|}{\Gamma(\varrho)|K_{1}|}} = 0.3262. \end{equation*} |
It is clear that \vert\Phi(t, \chi)\vert \leq 0.0586\leq 0.3262 whenever \chi\in [-32.5927, 32.5927] . Therefore, by Theorem 3.2, we find out that the discrete FBVP (5.5) has a solution.
We proved existence and uniqueness of solution to discrete fractional boundary value problems (FBVPs) involving fractional difference operators via the Brouwer fixed point theorem and the Banach contraction principle. Different versions of stability criteria were obtained for a discrete FBVP involving Riemann-Liouville difference operators. The results were illustrated by suitable examples. The approach of this paper is new and can be a beginning method for discussing different real-world models in the context of discrete behavior structures. In particular, our results can contribute for the development of discrete fractional boundary value problems describing discrete dynamics of some physical applications. In future works, we plan to extend our approach to other types of discrete differential inclusions or fully-hybrid discrete fractional differential equations.
The third and fourth authors would like to thank Azarbaijan Shahid Madani University. The fifth author was supported by the Portuguese Foundation for Science and Technology (FCT) and CIDMA through project UIDB/04106/2020. This research received funding support from the NSRF via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation (Grant number B05F650018).
The authors declare no conflict of interest.
[1] |
Kurande V, Waagepetersen R, Toft E, et al. (2012) Repeatability of Pulse Diagnosis and Body Constitution Diagnosis in Traditional Indian Ayurveda Medicine. Global advances in health and medicine 1: 36–42. https://doi.org/10.7453/gahmj.2012.1.5.011 doi: 10.7453/gahmj.2012.1.5.011
![]() |
[2] |
Roopini N, Shivaram JM, Shridhar D (2015) Design & Development of a System for Nadi Pariksha. International Journal of Engineering Research Technology (IJERT) 4: 465‒470. http://dx.doi.org/10.17577/IJERTV4IS060509 doi: 10.15623/ijret.2015.0406080
![]() |
[3] | Narayanan C, Kumar AD, Priyadharshini S, et al. (2015) Cardiac Disorder Diagnosis through Nadi (Pulse) using Piezo Electric Sensors. International Journal of Multidisciplinary Research and Modern Education (IJMRME) 1: 209‒214. |
[4] | Lad V (2007) Secrets of the Pulse: The ancient art of Ayurvedic pulse diagnosis. 2 Eds., Delhi: Motilal Banarsidass Publishing House. |
[5] |
Navghare S, Bajaj P (2018) Design of Non-Invasive Pulse Rate Detector using LabVIEW. International Journal of Computer Applications 181: 19‒24. http://dx.doi.org/10.5120/ijca2018917811 doi: 10.5120/ijca2018917811
![]() |
[6] |
Anu S, Devi R, Keerthana R, et al. (2015) PC based Monitoring of Human Pulse Signal using LabVIEW. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering 3: 186‒187. http://dx.doi.org/10.17148/IJIREEICE.2015.3344 doi: 10.17148/IJIREEICE.2015.3344
![]() |
[7] |
Kalange AE, Gangal SA (2007) Piezoelectric Sensor for Human Pulse Detection. Defence Sci J 57: 109‒114. https://doi.org/10.14429/dsj.57.1737 doi: 10.14429/dsj.57.1737
![]() |
[8] |
Pavana MG, Shashikala N, Joshi M (2016) Design, development and comparative performance analysis of Bessel and Butterworth filter for Nadi Pariksha Yantra. 2016 IEEE International Conference on Engineering and Technology (ICETECH), 1068‒1072. https://doi.org/10.1109/ICETECH.2016.7569413 doi: 10.1109/ICETECH.2016.7569413
![]() |
[9] |
Kalange AE, Mahale BP, Aghav ST, et al. (2012) Nadi Parikshan Yantra and analysis of radial pulse. 1st International Symposium on Physics and Technology of Sensors (ISPTS-1), 165‒168. https://doi.org/10.1109/ISPTS.2012.6260910 doi: 10.1109/ISPTS.2012.6260910
![]() |
[10] |
Yoon YZ, Lee MH, Soh KS (2000) Pulse type classification by varying contact pressure. IEEE Eng Med Biol 19: 106‒110. https://doi.org/10.1109/51.887253 doi: 10.1109/51.887253
![]() |
[11] |
Sorvoja H, Kokko VM, Myllyla R, et al. (2005) Use of EMFi as a blood pressure pulse transducer. IEEE Transactions on Instrumentation and Measurement 54: 2505‒2512. https://doi.org/10.1109/TIM.2005.853345 doi: 10.1109/TIM.2005.853345
![]() |
[12] |
Chaudhari S, Mudhalwadkar R (2017) Nadi pariksha system for health diagnosis. International Conference on Intelligent Computing and Control (I2C2), 1‒4. https://doi.org/10.1109/I2C2.2017.8321935 doi: 10.1109/I2C2.2017.8321935
![]() |
[13] |
Škraba A, Koložvari A, Kofjač D, et al. (2019) Prototype of Group Heart Rate Monitoring with ESP32. 8th Mediterranean Conference on Embedded Computing (MECO), 1‒4. https://doi.org/10.1109/MECO.2019.8760150 doi: 10.1109/MECO.2019.8760150
![]() |
[14] |
Khaire NN, Joshi YV (2015) Diagnosis of Disease Using Wrist Pulse Signal for classification of pre-meal and post-meal samples. International Conference on Industrial Instrumentation and Control (ICIC), 866‒869. https://doi.org/10.1109/IIC.2015.7150864 doi: 10.1109/IIC.2015.7150864
![]() |
[15] |
Khandai SK, Jain SK (2017) Comparison of sensors performance for the development of wrist pulse acquisition system. TENCON 2017 IEEE Region 10 Conference, 2870‒2875. https://doi.org/10.1109/TENCON.2017.8228351. doi: 10.1109/TENCON.2017.8228351
![]() |
[16] |
Lee J, Kim J, Lee M (2001) Design of Digital Hardware System for Pulse Signals. J Med Syst 25: 385–394. https://doi.org/10.1023/A:1011975727571 doi: 10.1023/A:1011975727571
![]() |
[17] | Krishnan S, Abudhahir A (2016) Development of system to acquire Radial Artery Pulse for Objective Pain Measurement. Biomedicine 36: 35‒40. |
[18] |
Joshi A, Kulkarni A, Chandran S, et al. (2007) Nadi Tarangini: A Pulse Based Diagnostic System. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2207‒2210. https://doi.org/10.1109/IEMBS.2007.4352762 doi: 10.1109/IEMBS.2007.4352762
![]() |
[19] |
Pereira T, Paiva JS, Correia C, et al. (2016) An automatic method for arterial pulse waveform recognition using KNN and SVM classifiers. Med Biol Eng Comput 54: 1049–1059. https://doi.org/10.1007/s11517-015-1393-5 doi: 10.1007/s11517-015-1393-5
![]() |
[20] |
Rao S, Rao R (2015) Investigation on pulse reading using flexible pressure sensor. International Conference on Industrial Instrumentation and Control (ICIC), 213‒216. https://doi.org/10.1109/IIC.2015.7150740 doi: 10.1109/IIC.2015.7150740
![]() |
[21] |
Valsalan P, Baomar TA, Baabood AH (2020) IOT Based Health Monitoring System. Journal of Critical Reviews 7: 739‒743. https://doi.org/10.31838/jcr.07.04.137 doi: 10.31838/jcr.07.04.137
![]() |
[22] | Murphy J, Gitman Y, Pulse Sensor. Open Hardware. Available from: https://pulsesensor.com/pages/open-hardware |
[23] |
Sareen M, Kumar M, Santhosh J, et al. (2009) Nadi Yantra: a robust system design to capture the signals from the radial artery for assessment of the autonomic nervous system non-invasively. Journal of Biomedical Science and Engineering 2: 471‒479. https://doi.org/10.4236/jbise.2009.27068 doi: 10.4236/jbise.2009.27068
![]() |
[24] | Thakker B, Vyas AL (2009) Outlier Pulse Detection and Feature Extraction for Wrist Pulse Analysis. International Journal of Biomedical and Biological Engineering 3: 127‒130. |
[25] | Highlights of Nadi Tarangini. Available from: https://www.naditarangini.com/nadi-tarangini-device/ |
[26] |
Das S, Namasudra S (2022) A novel hybrid encryption method to secure healthcare data in IoT-enabled healthcare infrastructure. Comput Electr Eng 101: 107991. https://doi.org/10.1016/j.compeleceng.2022.107991 doi: 10.1016/j.compeleceng.2022.107991
![]() |
[27] |
Gupta A, Namasudra S (2022) A novel technique for accelerating live migration in cloud computing, Automat Softw Eng 29: 1‒21. https://doi.org/10.1007/s10515-022-00332-2 doi: 10.1007/s10515-021-00310-0
![]() |
[28] |
Das S, Namasudra S (2022) MACPABE: Multi authority-based CP-ABE with efficient attribute revocation for IoT-enabled healthcare infrastructure. Int J Netw Manag, e2200. https://doi.org/10.1002/nem.2200 doi: 10.1002/nem.2200
![]() |
[29] |
Kumar A, Abhishek K, Namasudra S, et al. (2021) A novel elliptic curve cryptography based system for smart grid communication. Int J Web Grid Serv 17: 321‒342. https://doi.org/10.1504/IJWGS.2021.10040914 doi: 10.1504/IJWGS.2021.118398
![]() |
[30] | Bawankar BU, Dharmik RC, Telrandhe S (2021) Nadi pariksha: IOT-based patient monitoring and disease prediction system. InJournal of Physics: Conference Series 1913: 012124. IOP Publishing. https://doi.org/10.1088/1742-6596/1913/1/012124 |
[31] | Kashyap M, Jain S (2022) Importance of Pulse Examination and Its Diagnostic System. In Recent Innovations in Computing, 189‒199. Springer, Singapore. https://doi.org/10.1007/978-981-16-8248-3_16 |
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