
Consumption of nine different natural resources has kept an increasing trend in Central African countries from 1970 to 2018. This study therefore, investigates the changes and major determinants that have driven the patterns of resource use in six Central African countries over almost fifty years. We used the logarithmic mean Divisia index (LMDI) method to quantitatively analyze different effects of technology, affluence and population associated with domestic material consumption (DMC) of Cameroon, Chad, Central African Republic, Equatorial Guinea, Democratic Republic of the Congo and Gabon from 1970 to 2018. We further subdivided the affluence effect into energy productivity (GDP/energy) and per capita energy use (energy/cap) and conducted a four-factor LMDI analysis of Cameroon as a case study. The results highlight that decreased affluence during certain periods has slowed down DMC growth in four of six Central African countries except for Cameroon and Equatorial Guinea, while significant technology offset in Equatorial Guinea reduces DMC growth by 28%. Population remains the main positive driving factor of DMC growth, with the highest share in the Democratic Republic of the Congo. The case of Cameroon shows that technological intensity and energy intensity play different roles in changing DMC. This study confirms that the rising population and economic growth, combined with a gradual improvement in technology in the region are insufficient to reduce natural resource use. A stringent management plan of natural resources for Central African countries should focus on technological improvement while remaining balanced with the future demand for socioeconomic development in the coming decades.
Citation: Yvette Baninla, Qian Zhang, Xiaoqi Zheng, Yonglong Lu. Drivers of changes in natural resources consumption of Central African countries[J]. Clean Technologies and Recycling, 2022, 2(2): 80-102. doi: 10.3934/ctr.2022005
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Consumption of nine different natural resources has kept an increasing trend in Central African countries from 1970 to 2018. This study therefore, investigates the changes and major determinants that have driven the patterns of resource use in six Central African countries over almost fifty years. We used the logarithmic mean Divisia index (LMDI) method to quantitatively analyze different effects of technology, affluence and population associated with domestic material consumption (DMC) of Cameroon, Chad, Central African Republic, Equatorial Guinea, Democratic Republic of the Congo and Gabon from 1970 to 2018. We further subdivided the affluence effect into energy productivity (GDP/energy) and per capita energy use (energy/cap) and conducted a four-factor LMDI analysis of Cameroon as a case study. The results highlight that decreased affluence during certain periods has slowed down DMC growth in four of six Central African countries except for Cameroon and Equatorial Guinea, while significant technology offset in Equatorial Guinea reduces DMC growth by 28%. Population remains the main positive driving factor of DMC growth, with the highest share in the Democratic Republic of the Congo. The case of Cameroon shows that technological intensity and energy intensity play different roles in changing DMC. This study confirms that the rising population and economic growth, combined with a gradual improvement in technology in the region are insufficient to reduce natural resource use. A stringent management plan of natural resources for Central African countries should focus on technological improvement while remaining balanced with the future demand for socioeconomic development in the coming decades.
As is well known, in the practical application of neural networks (NNs), it is often necessary to use and design NN models with different dynamic characteristics for different application scenarios and purposes. Therefore, the study of the dynamic behavior of NNs has become an important issue that is widely concerned in both theoretical research and practical applications of NNs. Therefore, the dynamics of various types of NNs, especially numerous classical NNs such as recurrent NNs [1,2], bidirectional associative memory NNs [3], inertial NNs [4,5], Hopfield NNs [6], Cohen-Grossberg NNs [7], etc., have been widely studied. It should be mentioned here that due to the stronger approximation, faster convergence speed, larger storage capacity, and higher fault tolerance of high-order NNs compared to low-order NNs, the dynamics research of high-order NNs has received widespread attention [8,9,10,11,12].
Meanwhile, owing to the fact that algebra-valued NNs, such as complex-valued [13,14], quaternion-valued [15,16,17,18], Clifford-valued [19,20,21,22,23], and octonion-valued NNs [24,25,26], are extensions of real-valued NNs and have more advantages than real-valued NNs in many application scenarios, research on the dynamics of algebra-valued NNs has gradually become a new hotspot in the field of NN research in recent years. It is worth mentioning here that the Clifford-valued high-order Hopfield fuzzy NN represents a sophisticated integration of Clifford algebra, high-order synaptic connections, and fuzzy logic, enabling it to achieve advanced applications in multidimensional data processing and complex system modeling. For example, it has applications in the fields of multidimensional signal processing, secure communication and image encryption, optimization and control systems, neuroscience, and cognitive modeling [27,28,29,30].
On the one hand, from both theoretical and practical perspectives, NN models with time-varying connection weights and time-varying external inputs are more realistic than those with constant connection weights and constant external inputs. Meanwhile, time delay effects are inevitable. As a result, the rate of change in the state of a neuron depends not only on its current state but also on its historical state, and even more so, on the rate of change in its historical state. It is precisely for these reasons that researchers have proposed various neutral-type NN models with D operators and conducted extensive research on their dynamics [31,32,33,34]. In addition, fuzzy logic and NNs complement each other: fuzzy systems provide interpretability and handle uncertainty, while NNs offer powerful learning from data. Their integration bridges the gap between data-driven machine learning and human-like reasoning, making systems more adaptable, transparent, and robust in real-world applications. Indeed, fuzzy NNs have been successfully applied in many fields such as signal processing, pattern recognition, associative memory, and image processing [35,36,37,38,39].
On the other hand, as is well known, almost periodic oscillation is an important dynamic of NNs with time-varying connection weights and time-varying external inputs. In the past few decades, the almost periodic oscillations of various NNs have been studied by countless scholars [23,31,33,34]. We know that besides Bohr's concept of almost periodicity, there are also Stepanov almost periodicity, Weyl almost periodicity, Besicovitch almost periodicity, and so on [40]. It should be pointed out here that Besicovitch almost periodicity is the most complex almost periodicity among Bohr almost periodicity, Stepanov almost periodicity, and Weyl almost periodicity, and that Stepanov almost periodicity, Weyl almost periodicity, and Besicovitch almost periodicity are referred to as generalized almost periodicity. Meanwhile, it should be noted that the product of two generalized almost periodic functions in the same sense may not necessarily be a generalized almost periodic function in that sense. Because of this reason, the emergence of high-order terms in high-order NNs poses difficulties for studying the generalized almost periodic oscillations of high-order NNs. As a consequence, the results of generalized almost periodic oscillations for high-order NNs are still very rare. Thereupon, it is necessary to further study the generalized almost periodic oscillation problem of high-order NNs.
Inspired by the above observations, this paper considers a class of Clifford-valued high-order Hopfield fuzzy NNs with time-varying delays and D operators as follows:
[xi(t)−ai(t)xi(t−τi(t))]′=−bi(t)xi(t)+n∑j=1cij(t)fj(xj(t))+n∑j=1uij(t)fj(xj(t−σij(t)))+n∑j=1γij(t)μj(t)+v∑j=1n∑k=1θijk(t)gj(xj(t−δijk(t)))gk(xk(t−δijk(t)))+n⋀j=1αij(t)fj(xj(t−ηij(t)))+n⋁j=1βij(t)fj(xj(t−ηij(t)))+n⋀j=1n⋀k=1qijk(t)gj(xj(t−δijk(t)))gk(xk(t−δijk(t)))+n⋁j=1n⋁k=1νijk(t)gj(xj(t−δijk(t)))gk(xk(t−δijk(t)))+n⋀j=1Tij(t)μj(t)+n⋁j=1Sij(t)μj(t)+Ii(t), | (1.1) |
where i∈J:={1,2,⋯,n}, xi(t)∈A indicates the state of the ith unit at time t; A is a real Clifford algebra; bi(t)∈A represents the self feedback coefficient at time t; αij(t),βij(t),Tij(t),Sij(t)∈A stand for the elements of the fuzzy feedback MIN template and fuzzy feed forward MAX template, respectively; ai(t),cij(t),uij(t) and θijk(t),qijk(t),νijk(t)∈A represent the first-order and second-order connection weights of the NN; γij(t) stands for the element of the feed forward template; ⋀ and ⋁ denote the fuzzy AND and OR operations, respectively; μj(t)∈A represents the input of the jth neuron; Ii(t)∈A corresponds to the external input to the ith unit; fj and gj:A→A signify the nonlinear activation functions; and τi(t),σij(t),ηij(t),δijk(t)∈R+ denote the transmission delays.
The initial value condition associated with (1.1) is given as
xi(s)=φi(s),s∈[−ϱ,0],i∈J, | (1.2) |
where φi∈BC([−ϱ,0],A),ϱ=maxi,j,k∈J{supt∈Rτi(t),supt∈Rσij(t),supt∈Rηij(t),supt∈Rδijk(t)}.
The main purpose of this paper is to investigate the existence and stability of Besicovitch almost periodic solutions for system (1.1). The main contributions of this paper are as follows:
1. This paper is the first one to investigate the existence of Besicovitch almost periodic solutions for system (1.1), and the results of this paper still hold true and are new in the following special cases of system (1.1).
(ⅰ) System (1.1) is a real-valued, complex-valued, or quaternion-valued system.
(ⅱ) System (1.1) is a real-valued, complex-valued, or quaternion-valued system without D operators, i.e. ai(t)=0.
(ⅲ) System (1.1) is a real-valued system without D operators and fuzzy terms, i.e., ai(t)=αij(t)=qijk(t)=νijk(t)=Tij(t)=Sij(t)≡0.
2. The research method proposed in the paper can be used to study the generalized almost periodic dynamics for other high-order NNs.
Remark 1.1. The method we propose can be summarized as follows: First, we use the fixed point theorem to prove the existence of solutions for system (1.1) that are bounded and continuous with respect to the Besicovitch seminorm on a closed subset of an appropriate Banach space. Then, we apply the definition and inequality techniques to prove that this solution is Besicovitch almost periodic.
The remaining part of the paper is arranged as follows: In the second section, we review some relevant concepts, introduce some symbols used in this article, cite a useful lemma, and state and prove the completeness of the space we will use. In the third section, we investigate the existence and stability of Besicovitch almost periodic solutions for system (1.1). In the fourth section, we provide an example to demonstrate the correctness of our results. Finally, in the fifth section, we provide a brief conclusion.
Let A={∑A∈ΩxAeA∈R} indicate a real Clifford algebra over Rm [41], where Ω={∅,1,2,⋯,A,⋯,12,⋯,m}, eA=eh1eh2⋯ehv, 1≤h1<h2<⋯<hv≤m, and in addition, e∅=e0=1, and eh, h=1,2,⋯,m are said to be Clifford generators and satisfy ep=1,p=0,1,2,⋯,s,e2p=−1,p=s+1,s+2,⋯,m, where s<m, and epeq+eqep=0,p≠q,p,q=1,2,⋯,m. For every x=∑A∈ΩxAeA∈A and y=(y1,y2,⋯,yn)T∈An, we define |x|1=maxA∈Ω{|xA|} and |y|n=maxi∈J{|yi|1}, respectively, and then the spaces (A,|⋅|1) and (An,|⋅|) are Banach ones.
Since there is no order relation among Clifford numbers, as in [42], for x=∑A∈ΩxAeA,y=∑A∈ΩyAeA, we define x⋀y=∑A∈Ω(min{xA,yA})eA and x⋁y=∑A∈Ω(max{xA,yA})eA. According to this regulation, for example, regarding the 6th and 7th terms on the right-hand side of Equation (1.1), we have
n⋀j=1αij(t)fj(xj(t−ηij(t)))=∑A∈Ω(min1≤j≤n{αAij(t)fAj(xj(t−ηij(t)))})eA |
and
n⋁j=1βij(t)fj(xj(t−ηij(t)))=∑A∈Ω(max1≤j≤n{αAij(t)fAj(xj(t−ηij(t)))})eA. |
For x=∑A∈ΩxAeA∈A, we indicate xc=x−x∅.
For the sake of generality in the subsequent discussion of this section, let (X,‖⋅‖) be a Banach space and Lploc(R,X) with 1≤p<+∞ be the space consisting of measurable and locally p-integrable functions from R into X. In the next section, we will take X=R, X=A, or X=An.
Definition 2.1. [40] A bounded continuous function φ:R→X is said to be almost periodic, if for every ε>0, there exists a number ℓ(ε)>0 such that for each a∈R, there exists a point σ∈[a,a+ℓ] satisfying
‖φ(t+σ)−φ(t)‖<ε. |
The family of such functions will be signified by AP(R,X).
For φ∈Lploc(R,X), the Besicovitch seminorm is defined as the following:
‖φ‖Bp={¯liml→∞12l∫l−l‖φ(t)‖pdt}1p. |
Definition 2.2. [43] A function φ∈Lploc(R,X) is called Bp-continuous if limh→0‖φ(⋅+h)−φ(⋅)‖Bp=0 and is called Bp-bounded if ‖φ‖Bp<∞.
Henceforth, we will denote the set of all functions that are Bp-continuous and Bp-bounded by BCBp(R,X).
Definition 2.3. [40] A function φ∈Lploc(R,X) is said to be Besicovitch almost periodic, if for every ε>0, there exists a positive number ℓ>0 such that for each a∈R, there exists a point σ∈[a,a+ℓ] satisfying
‖φ(⋅+σ)−φ(⋅)‖Bp<ε. |
Denote by BpAP(R,X) the class of such functions and, for simplicity, call them Bp-almost periodic functions.
Lemma 2.1. [44] If αij,βij∈C(R,A),gj∈C(A,A),i,j∈J, then one has
|n⋀i=1αij(t)gj(x)−n⋀i=1αij(t)gj(y)|1≤n∑i=1|αij(t)‖‖gj(x)−gj(y)|1,|n⋁i=1βij(t)gj(x)−n⋁i=1βij(t)gj(y)|1≤n∑i=1‖βij(t)‖|gj(x)−gj(y)|1. |
Let L∞(R,X) be the set of all essentially bounded measurable functions from R to X, then (L∞(R,X),‖⋅‖∞) is a Banach space, where ‖⋅‖∞:=esssupt∈R‖⋅‖ denotes the essential supremum norm.
Denote
Z={x|x∈L∞(R,X)∩BCBp(R,X)}. |
Then we have the following lemma which is crucial for the proof of our main result of this paper.
Lemma 2.2. The space (Z,‖⋅‖∞) is a Banach space.
Proof. Let {ϕn}⊂Z be a Cauchy sequence, and then for every ε>0, there is a positive integer N1 such that for n,m>N1,
‖ϕn(⋅)−ϕm(⋅)‖∞<ε3. |
Since {ϕn}⊂Z⊂L∞(R,X) and (L∞(R,X),‖⋅‖∞) is a Banach space, there exists ϕ∈L∞(R,An) such that ϕn→ϕ as n→∞ with respect to the norm ‖⋅‖∞. To complete the proof, it suffices to prove that ϕ∈BCBp(R,X). From limn→∞ϕn=ϕ in regard to the essential supremum norm, it follows that there exists a positive integer N2 such that for n>N2,
‖ϕn(⋅)−ϕ(⋅)‖∞<ε3. |
Now, take N0=max{N1,N2}, and then, due to the fact that ϕN0+1∈BCBp(R,X), there exists a δ=δ(ε)>0 such that for any h∈R with |h|<ε, it holds that
‖ϕN0+1(⋅+h)−ϕN0+1(⋅)‖Bp<ε3. |
Consequently,
‖ϕ(⋅+h)−ϕ(⋅)‖Bp≤‖ϕ(⋅+h)−ϕN0+1(⋅+h)‖Bp+‖ϕN0+1(⋅+h)−ϕN0+1(⋅)‖Bp+‖ϕN0+1(⋅)−ϕ(⋅)‖Bp≤‖ϕ(⋅+h)−ϕN0+1(⋅+h)‖∞+‖ϕN0+1(⋅+h)−ϕN0+1(⋅)‖Bp+‖ϕN0+1(⋅)−ϕ(⋅)‖∞≤ε3+ε3+ε3=ε, |
which implies ϕ∈BCBp(R,X). The proof is completed.
In this section, for x∈L∞(R,A), we denote |x|∞=maxA∈Ω{esssupt∈R|xA(t)|} and for z=(z1,z2,⋯,zn)T=(∑AzA1eA,∑AzA2eA,⋯,∑AzAneA)T∈L∞(R,An), we denote ‖z‖∞=maxi∈J{|zi|∞}. Let Z={z|z∈L∞(R,An)∩BCBp(R,An)}, and then, according to Lemma 2.2, (Z,‖⋅‖∞) is a Banach space. For x∈BpAP(R,A) and z∈BpAP(R,An), we will use |x|Bp and ‖z‖Bp to represent the seminorms of x and z, respectively.
In what follows, we will employ the following symbols:
ˉg=supt∈R‖g(t)‖Yandg_=inft∈R‖g(t)‖Y, |
where g:R→Y is a bounded function and (Y,‖⋅‖Y) is a normed space. Moreover, we will use the following assumptions:
(A1) For i,j,k∈J, functions b∅i∈AP(R,R+) with b_∅i>0, ai,bci,μj,cij,uij,αij,βij,θijk,qijk,νijk∈AP(R,A),τi,σij,ηij,δijk∈AP(R,R)∩C1(R,R+) with τ′i(t)≤ˉτ′i<1,σ′ij(t)≤ˉσ′ij<1,η′ij(t)≤ˉη′ij<1,δ′ijk(t)≤ˉδ′ijk<1, where ˉτ′,ˉσ′,ˉη′,ˉδ′ are constants, and γij,Tij,Sij,Ii∈L∞(R,A)∩BpAP(R,A).
(A2) For all j∈J, functions fj,gj∈C(A,A) with fj(0)=0,gj(0)=0, and there exist positive constants Lfj,Lgj,Mgj, and Mgk such that for any u,v∈A,
|fj(u)−fj(v)|1≤Lfj|u−v|1,|gj(u)−gj(v)|1≤Lgj|u−v|1,|gj(u)|1≤Mgj,|gk(u)|1≤Mgk. |
(A3) For i∈J, there exist positive constants ϑi such that
ρ:=maxi∈J{ˉai+1b_∅i[ˉb∅iˉai+ˉbci+ϑ−1i(n∑j=1ˉcijLfjϑj+n∑j=1ˉuijLfjϑj+n∑i=1n∑k=1ˉθijkLgjMgkϑj+n∑j=1ˉαijLfjϑj+n∑j=1ˉβijLfjϑj+n∑i=1n∑k=1ˉqijkLgjMgkϑj+n∑i=1n∑k=1ˉνijkLgjMgkϑj)]}<1. |
(A4) For the constants ϑi,i∈J, mentioned in (A3), and p,q>1 with 1p+1q=1, it holds that
P:=2p−1maxi∈J{4p−1(ˉai)p11−ˉτ′i+70p−1(1b_∅i)p+qq(ˉaiˉb∅i)peb_∅iˉτi1−ˉτ′i+70p−1(1b_∅i)p+qq(ˉbci)p+35p−1ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉcij)q)pqn∑j=1(Lfjϑj)p+70p−1ϑ−pi(1b_∅i)p+1q(n∑j=1(ˉuij)q)pq×n∑j=1(Lfjϑj)peb_∅iˉσij1−ˉσ′ij+140p−1ϑ−pi(1b_∅i)p+qqn2pq[n∑j=1n∑k=1(ˉθijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉθijkMgjLgkϑk)p]eb_∅iˉδijk1−ˉδ′ijk+70p−1ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉαij)q)pq×n∑j=1(Lfjϑj)peb_∅iˉηij1−ˉη′ij+70p−1ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉβij)q)pqn∑j=1(Lfjϑj)peb_∅iˉηij1−ˉη′ij+140p−1ϑ−pi(1b_∅i)p+qqn2pq(n∑j=1n∑k=1(ˉqijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉqijkMgjLgkϑk)p)×eb_∅iˉδijk1−ˉδ′ijk+140p−1ϑ−pi(1b_∅i)p+qqn2pq(n∑j=1n∑k=1(ˉνijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉνijkMgjLgkϑk)p)epqb_∅iˉδijk1−ˉδ′ijk}<1. |
For i∈J, let yi(t)=ϑ−1ixi(t),Zi(t)=yi(t)−ai(t)yi(t−τi(t)), where ϑi>0 are constants, and then system (1.1) turns into
Z′i(t)=−b∅i(t)Zi(t)−b∅i(t)ai(t)yi(t−τi(t))−bci(t)yi(t)+ϑ−1i[n∑j=1cij(t)fj(ϑjyj(t)+n∑j=1uij(t)fj(ϑjyj(t−σij(t)))+n∑j=1γij(t)μj(t)+n∑j=1n∑k=1θijk(t)gj(ϑjyj(t−δijk(t)))gk(ϑkyk(t−γijk(t)))+n⋀j=1αij(t)fj(ϑjyj(t−ηij(t)))+n⋁j=1βij(t)fj(ϑjyj(t−ηij(t)))+n⋀j=1n⋀k=1qijk(t)gj(ϑjyj(t−δijk(t)))gk(ϑkyk(t−δijk(t)))+n⋁j=1n⋁k=1νijk(t)gj(ϑjyj(t−δijk(t)))gk(ϑkyk(t−δijk(t)))+n⋀j=1Tij(t)μi(t)+n⋁j=1Sij(t)μi(t)+Ii(t)],i∈J. | (3.1) |
Multiplying both sides of (3.1) with e∫tt0b∅i(u)du and integrating over the interval [t0,t], then it holds that
yi(t)=ai(t)yi(t−τi(t))+[yi(t0)−ai(t0)yi(t0−τi(t0))]e−∫tt0b∅i(u)du+∫tt0e−∫tsb∅i(u)du(Ny)i(s)ds,i∈J, | (3.2) |
where
(Ny)i(s)=−b∅i(s)ai(s)yi(s−τi(s))−bci(s)yi(s)+ϑ−1i(n∑j=1cij(s)fj(ϑjyj(s))+n∑j=1uij(s)fj(ϑjyj(s−σij(s)))+n∑j=1γij(s)μj(s)+n∑j=1n∑k=1θijk(s)gj(ϑjyj(s−δijk(s)))gk(ϑkyk(s−δijk(s)))+n⋀j=1αij(s)fj(ϑjyj(s−ηij(s)))+n⋁j=1βij(s)fj(ϑjyj(s−ηij(s)))+n⋀j=1n⋀k=1qijk(s)gj(ϑjyj(s−δijk(s)))gk(ϑkyk(s−δijk(s)))+n⋁j=1n⋁k=1νijk(s)gj(ϑjyj(s−δijk(s)))gk(ϑkyk(s−δijk(s)))+n⋀j=1Tij(s)μi(s)+n⋁j=1Sij(s)μi(s)+Ii(s)). |
It is easy to verify that if y∗(t)=(y∗1(t),y∗2(t),⋯,y∗n(t)) solves system (3.1), then x∗(t)=(x∗1(t),x∗2(t),⋯,x∗n(t))=(ϑ−11y∗1(t),ϑ−12y∗2(t),⋯,ϑ−1ny∗n(t)) solves system (1.1).
Definition 3.1. A function x=(x1,x2,⋯,xn):R→An is called a solution of (1.1) provided that there exist positive numbers ϑi such that yi(t)=ϑ−1ixi(t),i∈J fulfill (3.2).
Set
ˆφ=(ˆφ1(t),ˆφ2(t),⋯,ˆφn(t))T, |
where
ˆφi(t)=∫t−∞e−∫tsb∅i(u)du(n∑j=1γij(s)μj(s)+n⋀j=1Tij(s)μj(s)+n⋁j=1Sij(s)μj(s)+Ii(s))ds,i∈J. |
It is easy to see that ˆφ is well defined under condition (A1). Choose a positive constant r with r>‖ˆφ‖∞.
Then, we are now in a position to present and prove our existence result.
Theorem 3.1. Assume that (A1)−(A4) hold. Then, system (1.1) admits a unique Bp-almost periodic solution in Z∗:={φ|φ∈Z,‖φ−ˆφ‖∞≤ρr1−ρ}.
Proof. Letting t0→∞, from (3.2), one gets
yi(t)=ai(t)yi(t−τi(t))+∫t−∞e−∫tsb∅i(u)du(Ny)i(s)ds,i∈J. |
Define a mapping T:Z∗→Z∗ by setting (Tφ)(t)=((Tφ)1(t),(Tφ)2(t),⋯,(Tφ)n(t))T for φ∈Z and t∈R, where (Tφ)i(t)=ai(t)φi(t−τi(t))+∫t−∞e−∫tsb∅i(u)du(Nφ)i(s)ds,i∈J.
To begin with, we show that T(Z∗)⊂Z∗.
Note that, for any φ∈Z∗, it holds that
‖φ‖∞≤‖φ−ˆφ‖∞+‖ˆφ‖∞≤ρr1−ρ+r=r1−ρ |
and ‖Nφ‖∞<∞.
For every φ∈Z∗, we infer that
‖Tφ−ˆφ‖∞=maxi∈J{esssupt∈R|ai(t)φi(t−τi(t))+∫t−∞e−∫tsb∅i(u)du[−b∅i(s)ai(s)φi(s−τi(s))−bci(s)φi(s)+ϑ−1i(n∑j=1cij(s)fj(ϑjφj(s))+n∑j=1uij(s)fj(ϑjφj(s−σij(s)))+n∑i=1n∑k=1θijk(s)gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s)))+n⋀j=1αij(s)fj(ϑjφj(s−ηij(s)))+n⋁j=1βij(s)fj(ϑjφj(s−ηij(s)))+n⋀j=1n⋀k=1qijk(s)gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s)))+n⋁j=1n⋀k=1νijk(s)gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s))))]ds|1}≤maxi∈J{ˉai‖φ‖∞+∫t−∞e−b_∅i(t−s)[ˉb∅iˉai+ˉbci+ϑ−1i(n∑j=1ˉcijLfjϑj+n∑j=1ˉuijLfjϑj+n∑i=1n∑k=1ˉθijkLgjMgkϑjϑk+n∑j=1ˉαijLfjϑj+n∑j=1ˉβijLfjϑj+n∑j=1n∑k=1ˉqijkLgjMgkϑjϑk+n∑j=1n∑k=1ˉνijkLgjMgkϑjϑk)]‖φ‖∞ds}≤maxi∈J{ˉai+1b_∅i(ˉb∅iˉai+ˉbci+n∑j=1ˉcijLfj+n∑j=1ˉuijLfj+n∑i=1n∑k=1ˉθijkLgjMgk+n∑j=1ˉαijLfj+n∑j=1ˉβijLfj+n∑i=1n∑k=1ˉqijkLgjMgk+n∑i=1n∑k=1ˉνijkLgjMgk)}‖φ‖∞=ρ‖φ‖∞<r1−ρ,i∈J. |
In addition, by condition (A1) and the fact that φ∈Z, we have that for every ε>0, there exists a positive number δ=δ(ε)(<ε) such that for any h∈R with |h|<δ, it holds
|ai(t+h)−ai(t)|1<ε,|φi(⋅+h)−φi(⋅)|Bp<ε,|τi(t+h)−τi(t)|<δ,i∈J. |
Without loss of generality, in the sequel, we assume that h>0, then we deduce that
‖Tφ(⋅+h)−Tφ(⋅)‖pBp≤2p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+h)φi(t+h−τi(t+h))−ai(t)φi(t−τi(t))|p1dt}+2p−1maxi∈J{¯liml→∞12l∫l−l|∫t+h−∞e−∫t+hsb∅i(u)du(Nφ)i(s)ds−∫t−∞e−∫tsb∅i(u)du(Nφ)i(s)ds|p1dt}≤6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+h)−ai(t)|p1|φi(t+h−τi(t+h))|p1dt}+6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t)|p1|φi(t+h−τi(t+h))−φi(t−τi(t+h))|p1dt}+6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t)|p1|φi(t−τi(t+h))−φi(t−τi(t))|p1dt}+4p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫t+hsb∅i(u)du−e−∫tsb∅i(u)du|(Nφ)i(s)ds|p1dt}+4p−1maxi∈J{¯liml→∞12l∫l−l|∫t+hte−∫t+hsb∅i(u)du(Nφ)i(s)ds|p1dt}≤6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+h)−ai(t)|p1|φi(t+h−τi(t+h))|p1dt}+6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t)|p1|φi(t+h−τi(t+h))−φi(t−τi(t+h))|p1dt}+6p−1maxi∈J{¯liml→∞12l∫l−l|ai(t)|p1|φi(t−τi(t+h))−φi(t−τi(t))|p1dt}+4p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−b_∅i(t−s)|∫t+hsb∅i(u)du−∫tsb∅i(u)du|(Nφ(s))ids|p1}+4p−1maxi∈J{¯liml→∞12l∫l−l|∫t+hte−∫t+hsb∅i(u)du(Nφ)i(s)ds|p1dt}≤maxi∈J{6p−1εp‖φ‖p∞+6p−1ˉapiεp+6p−1ˉapiεp+4p−1hp[(ˉb∅ib_∅i)p+(1b_∅i)p]‖Nφ‖p∞}≤maxi∈J{6p−1‖φ‖p∞+6p−1ˉai+6p−1ˉai+4p−1[(ˉb∅ib_∅i)p+(1b_∅i)p]‖Nφ‖p∞}εp, |
which implies Tφ∈BCBp(R,An). Therefore, T(Z∗)⊂Z∗.
Next, we will prove that T is a contraction mapping. In fact, for any φ,ψ∈Z∗,i∈J, we have
‖Tφ−Tψ‖∞≤esssupt∈R|ai(t)(φi(t−τi(t))−ψi(t−τi(t)))|1+esssupt∈R|∫t−∞e−∫tsb∅i(u)du[−b∅i(s)ai(s)(φi(s−τi(s))−ψi(s−τi(s)))−bci(s)(φi(s)−ψi(s))+ϑ−1i(n∑j=1cij(s)(fj(ϑjφj(s))−fj(ϑjψj(s)))+n∑j=1uij(s)(fj(ϑjφj(s−σij(s)))−fj(ϑjψj(s−σij(s))))+n∑i=1n∑k=1θijk(s)(gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s)))−gj(ϑjψj(s−δijk(s))))gk(ϑkψk(s−δijk(s))))+n∑j=1αij(s)(fj(ϑjφj(s−ηij(s)))−fj(ϑjψj(s−ηij(s))))+n∑j=1βij(s)(fj(ϑjφj(s−ηij(s)))−fj(ϑjψj(s−ηij(s))))+n∑i=1n∑k=1qijk(s)(gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s)))−gj(ϑjψj(s−δijk(s))))gk(ϑkψk(s−δijk(s))))+n∑i=1n∑k=1νijk(s)(gj(ϑjφj(s−δijk(s)))gk(ϑkφk(s−δijk(s)))−gj(ϑjψj(s−δijk(s))))gk(ϑkψk(s−δijk(s)))]ds≤ˉai‖φ−ψ‖∞+∫t−∞eb_∅i(t−s)[ˉb∅iˉai+ˉbci+ϑ−1i(n∑j=1ˉcijLfjϑj+n∑j=1ˉuijLfjϑj+n∑j=1n∑k=1ˉθijkLgjMgkϑj+n∑j=1ˉαijLfjϑj+n∑j=1ˉβijLfjϑj+n∑j=1n∑k=1ˉqijkLgjMgkϑj+n∑j=1n∑k=1ˉνijkLgjMgkϑj)]‖φ−ψ‖∞ds≤maxi∈J{ˉai+1b_∅i[ˉb∅iˉai+ˉbci+ϑ−1i(n∑j=1ˉcijLfjϑj+n∑j=1ˉuijLfjϑj+n∑i=1n∑k=1ˉθijkLgjMgkϑj+n∑j=1ˉαijLfjϑj+n∑j=1ˉβijLfjϑj+n∑i=1n∑k=1ˉqijkLgjMgkϑj+n∑i=1n∑k=1ˉνijkLgjMgkϑj)]}‖φ−ψ‖∞=ρ‖φ−ψ‖∞,i∈J, |
which combined with condition (A3) means that T is a contraction mapping. Thereupon, T has a unique fixed point φ∗∈Z∗.
Finally, we will examine that φ∗ is Bp-almost periodic.
Since φ∗∈Z∗⊂BCBp(R,An), for any ε>0, there exists a σ>0(σ<ε) such that, for any ℏ∈R with |ℏ|<σ,
|φ∗i(⋅+ℏ)−φ∗i(⋅)|Bp<ε,i∈J. |
Based on this and (A1), there exists ♭ such that, for all i∈J,
|ai(⋅+♭)−ai(⋅)|1<ε,|b∅i(⋅+♭)−b∅i(⋅)|<ε,|bci(⋅+♭)−bci(⋅)|1<ε, | (3.3) |
|cij(⋅+♭)−cij(⋅)|1<ε,|uij(⋅+♭)−uij(⋅)|1<ε,|γij(⋅+♭)−γij(⋅)|Bp<ε, | (3.4) |
|θijk(⋅+♭)−θijk(⋅)|1<ε,|αij(⋅+♭)−αij(⋅)|1<ε,|βij(⋅+♭)−βij(⋅)|1<ε, | (3.5) |
|qijk(⋅+♭)−qijk(⋅)|1<ε,|νijk(⋅+♭)−νijk(⋅)|1<ε,|Tij(⋅+♭)−Tij(⋅)|Bp<ε, | (3.6) |
|τi(t+♭)−τ(t)|<ε,|σij(t+♭)−σij(t)|<ε,|δijk(t+♭)−δijk(t)|<ε, | (3.7) |
|ηij(t+♭)−ηij(t)|<ε,|Sij(⋅+♭)−Sij(⋅)|Bp<ε,|Ii(⋅+♭)−Ii(⋅)|Bp<ε, | (3.8) |
|φ∗i(⋅−τi(⋅+♭))−φ∗i(⋅−τi(⋅))|Bp<ε,|φ∗j(⋅−σij(⋅+♭))−φ∗j(⋅−σij(⋅))|Bp<ε, | (3.9) |
|φ∗i(⋅−ηij(⋅+♭))−φ∗i(⋅−ηij(⋅))|Bp<ε,|φ∗j(⋅−δijk(⋅+♭))−φ∗j(⋅−δijk(⋅))|Bp<ε, | (3.10) |
|φ∗k(⋅−δijk(⋅+♭))−φ∗k(⋅−δijk(⋅))|Bp<ε. | (3.11) |
Then, we deduce that
‖φ∗(t+♭)−φ∗(t)‖pBp≤2p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+♭)φ∗i(t+♭−τi(t+♭))−ai(t)φ∗i(t−τi(t))|p1dt}+2p−1maxi∈J{¯liml→∞12l∫l−l|∫t+♭−∞e−∫t+♭sb∅i(u+♭)du(Nφ∗)i(s)ds−∫t−∞e−∫tsb∅i(u)du(Nφ∗)i(s)ds|p1dt}≤4p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+♭)(φ∗i(t+♭−τi(t+♭))−φ∗i(t−τi(t)))|p1dt}+4p−1maxi∈J{¯liml→∞12l∫l−l|(ai(t+♭)−ai(t))φ∗i(t−τi(t))|p1dt}+2p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(Nφ∗)i(s+♭)ds−∫t−∞e−∫tsb∅i(u)du(Nφ∗)i(s)ds|p1dt}≤4p−1maxi∈J{¯liml→∞12l∫l−l|ai(t+♭)(φ∗i(t+♭−τi(t+♭))−φ∗i(t−τi(t)))|p1dt}+4p−1maxi∈J{¯liml→∞12l∫l−l|(ai(t+♭)−ai(t))φ∗i(t−τi(t))|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)duai(s+♭)b∅i(s+♭)×(φ∗i(s+♭−τi(s+♭))−φ∗i(s−τi(s)))ds|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(ai(s+♭)−ai(s))b∅i(s+♭)×φ∗i(s−τi(s))ds|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)duai(s)(b∅i(s+♭)−b∅i(s))φ∗i(s−τi(s))ds|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−1|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×ai(s)b∅i(s)φ∗i(s−τi(s))ds|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(bci(s+♭)φ∗i(s+♭)−bci(s)φ∗i(s))ds|p1dt}+70p−1maxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|bci(s)φ∗i(s)ds|p1dt} |
+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1cij(s+♭)(fj(ϑjφ∗j(s+♭))−fj(ϑjφ∗i(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1(cij(s+♭)−cij(s))fj(ϑjφ∗j(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1cij(s)fj(ϑjφ∗j(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1uij(s+♭)×(fj(ϑjφ∗j(s+♭−σij(s+♭)))−fj(ϑjφ∗j(s−σij(s))))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1(uij(s+♭)−uij(s))×fj(ϑjφ∗j(s−σij(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1uij(s)fj(ϑjφ∗j(s−σij(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(n∑j=1γij(s+♭)μj(s+♭)−n∑j=1γij(s)μj(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|n∑j=1γij(s)μj(s)ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1θijk(s+♭)×(gj(ϑjφ∗j(s+♭−δijk(s+♭)))gk(ϑkφ∗k(s+♭−δijk(s+♭)))−gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s))))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1(θijk(s+♭)−θijk(s))gj(ϑjφ∗j(s−δijkk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1n∑k=1θijk(s)gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt} |
+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1αij(s+♭)×(fj(ϑjφ∗j(s+♭−ηij(s+♭)))−fj(ϑjφ∗j(s−ηij(s))))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1(αij(s+♭)−αij(s))×fj(ϑjφ∗j(s−ηjj(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1αij(s)fj(ϑjφ∗j(s−ηjj(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1βij(s+♭)×(fj(ϑjφ∗j(s+♭−ηij(s+♭)))−fj(ϑjφ∗j(s−ηij(s))))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1(βij(s+♭)−βij(s))×fj(ϑjφ∗j(s−ηjj(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1βij(s)fj(ϑjφ∗j(s−ηjj(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1qijk(s+♭)×(gj(ϑjφ∗j(s+♭−δijk(s+♭))gk(ϑkφ∗k(s+♭−δijk(s+♭)))−gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s))))ds|p1dt} |
+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1(qijk(s+♭)−qijk(s))gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{lim supl→∞(2l)−1∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1n∑k=1qijk(s)gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1νijk(s+♭)×(gj(ϑjφ∗j(s+♭−δijk(s+♭))gk(ϑkφ∗k(s+♭−δijk(s+♭)))−gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s))))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)dun∑j=1n∑k=1(νijk(s+♭)−νijk(s))gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|×n∑j=1n∑k=1νijk(s)gj(ϑjφ∗j(s−δijk(s)))gk(ϑkφ∗k(s−δijk(s)))ds|p1dt} |
+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(n∑j=1Tij(s+♭)μj(s+♭)−n∑j=1Tij(s)μj(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|n∑j=1Tij(s)μj(s)ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(n∑j=1Sij(s+♭)μj(s+♭)−n∑j=1Sij(s)μj(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|n∑j=1Sij(s)μj(s)ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞e−∫tsb∅i(u+♭)du(Ii(s+♭)−Ii(s))ds|p1dt}+70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l|∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|Ii(s)ds|p1dt}:=37∑i=1Ki. |
Furthermore, based on inequalities (3.3)–(3.11), the Hölder inequality, and the Fubini theorem, we can deduce that
K1≤8p−1maxi∈J{¯liml→∞12l[∫l−l|ai(t+♭)|p(|φ∗i(t+♭−τi(t+♭))−φ∗i(t−τi(t+♭))|p1+|φ∗i(t−τi(t+♭))−φ∗i(t−τi(t))|p1)dt}≤8p−1maxi∈J{(ˉai)p11−¯τ′i|φ∗i(t+♭)−φ∗i(t)|pBp+(ˉai)pεp},K2≤4p−1maxi∈J{‖φ∗‖p∞εp},K3≤140p−1maxi∈J{¯liml→∞12l∫l−l[∫t−∞e−∫tsb∅i(u+♭)duds]pq∫t−∞e−∫tsb∅i(u+♭)du×|ai(s+♭)b∅i(s+♭)|1(|φ∗i(s+♭−τi(s+♭))−φ∗i(s−τi(s+♭))|p1+|φ∗i(s−τi(s+♭))−φ∗i(s−τi(s))|p1)dsdt}≤140p−1maxi∈J{(1b_∅i)pq(ˉaiˉb∅i)p[¯liml→∞12l∫l−l∫t−τi(t+♭)−∞e−b_∅i(t−s−ˉτi)1−ˉτ′i×|φ∗i(s+♭)−φ∗i(s)|p1dsdt]+εpb_∅i}≤140p−1maxi∈J{(1b_∅i)pq(ˉaiˉb∅i)p[eb_∅iˉτi1−¯τ′i¯liml→∞12l∫l−l∫t−∞e−b_∅i(t−s)×|φ∗i(s+♭)−φ∗i(s)|p1dsdt]+εpb_∅i}≤140p−1maxi∈J{(1b_∅i)pq(ˉaiˉb∅i)p[eb_∅iˉτi1−¯τ′i¯liml→∞12l∫l−∞(2l)−1∫ss−2le−b_∅i(l−s)×|φ∗i(t+♭)−φ∗i(t)|p1dtds]+εpb_∅i}≤140p−1maxi∈J{(1b_∅i)p+qq(ˉaiˉb∅i)p(eb_∅iˉτi1−¯τ′i‖φ∗(t+♭)−φ∗(t)‖pBp+εp)},K4≤70p−1maxi∈J{¯liml→∞12l∫l−l(∫t−∞e−∫tsb∅i(u+♭)duds)pq×∫t−∞e−∫tsb∅i(u+♭)du|(ai(s+♭)−ai(s))b∅i(s+♭)φ∗i(s−τi(s))|p1dsdt}≤70p−1maxi∈J{(1b_∅i)p+qq(ˉb∅i)p‖φ∗‖p∞εp}.K5≤70p−1maxi∈J{(1b_∅i)p+qq(ˉai)p‖φ∗‖p∞εp},K6≤70p−1maxi∈J{¯liml→∞12l∫l−1[∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|ds]pq×∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du||ai(s)b∅i(s)φ∗i(s−τi(s))|p1dsdt}≤70p−1maxi∈J{(1b_∅i)2(p+q)q(ˉaiˉb∅i)p‖φ∗‖p∞εp+qq},K7≤70p−1maxi∈J{¯liml→∞12l∫l−l[∫t−∞e−∫tsb∅i(u+♭)duds]pq×∫t−∞e−∫tsb∅i(u+♭)du|bci(s+♭)φ∗i(s+♭)−bci(s)φ∗i(s)|p1dsdt}≤140p−1maxi∈J{(1b_∅i)pq¯liml→∞12l∫l−∞e−b_∅i(l−s)∫ss−2l((ˉbci)p |
×|φ∗i(t+♭)−φ∗i(t)|p1+|bci(t+♭)−bci(t)|p1‖φ∗‖p∞)dtds}≤140p−1maxi∈J{(1b_∅i)p+qq((ˉbci)p‖φ∗(t+♭)−φ∗(t)‖pBp+‖φ∗‖p∞εp)},K8≤70p−1maxi∈J{(1b_∅i)2(p+q)q(ˉb∅i)p‖φ∗‖p∞εp+qq},K9≤70p−1maxi∈J{ϑ−pi¯liml→∞12l∫l−l[∫t−∞e−∫tsb∅i(u+♭)duds]pq×∫t−∞e−∫tsb∅i(u+♭)du|n∑j=1cij(s+♭)(fj(ϑjφ∗j(s+♭))−fj(ϑjφ∗i(s)))|p1dsdt}≤70p−1maxi∈J{ϑ−pi(1b_∅i)pq(n∑j=1(ˉcij)q)pqn∑j=1(Lfjϑj)p¯liml→∞12l∫l−∞e−b_∅i(l−s)×∫ss−2l|φ∗j(t+♭))−φ∗i(t)|p1dtds}≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉcij)q)pqn∑j=1(Lfjϑj)p‖φ∗(t+♭))−φ∗(t)‖pBp},K10≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqnpqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp},K11≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉcij)q)pqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp+qq},K12≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+1q(n∑j=1(ˉuij)q)pqn∑j=1(Lfjϑj)p×[eb_∅iˉσij1−¯σ′ij‖φ∗(t+♭)−φ∗(t)‖pBp+εp]}, |
K13≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn∑j=1(Lfjϑj)pnpq‖φ∗‖p∞εp},K14≤70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l[∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|qpds]pq×∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|pq|n∑j=1uij(s)fj(ϑjφ∗j(s−σij(s)))|p1dsdt}≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉuij)q)pqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp+qq},K15≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+qq[n∑j=1(ˉμj)p+n∑j=1|γij|p∞]εp},K16≤70p−1ϑ−pimaxi∈J{¯liml→∞12l∫l−l[∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|qpds]pq×∫t−∞|e−∫tsb∅i(u+♭)du−e−∫tsb∅i(u)du|pq|n∑j=1γij(s)μj(s)|p1dsdt}≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q(n∑j=1|γij|q∞)pqn∑j=1(ˉμj)pεp+qq},K17≤70p−1maxi∈J{ϑ−pi¯liml→∞12l∫l−l(∫t−∞e−∫tsb∅i(u+♭)duds)pq∫t−∞e−∫tsb∅i(u+♭)du×(n∑j=1n∑k=1ˉθijk(Mgk|gj(ϑjφ∗j(s+♭−δijk(s+♭)))−gj(ϑjφ∗j(s−δijk(s)))|1+Mgj|gk(ϑkφ∗k(s+♭−δijk(s+♭)))−gk(ϑkφ∗k(s−δijk(s))))|1)dsdt)p}≤280p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pq[n∑j=1n∑k=1(ˉθijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉθijkMgjLgkϑk)p]×(eb_∅iˉδijk1−¯δ′ijk‖φ∗(t+♭)−φ∗(t)‖pBp+εp)},K18≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pqn∑k=1n∑j=1(MgjMgk)pεp},K19≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)pn2pqn∑j=1n∑k=1(ˉθijkMgjMgk)pεp+qq},K20≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉαij)q)pqn∑j=1(Lfjϑj)p×[eb_∅iˉηij1−¯η′ij‖φ∗(t+♭)−φ∗(t)‖pBp+εp]},K21≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqnpqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp}, |
K22≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉαij)q)pqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp+qq},K23≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉβij)q)pqn∑j=1(Lfjϑj)p×[eb_∅iˉηij1−¯η′ij‖φ∗(t+♭)−φ∗(t)‖pBp+εp]},K24≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqnpqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp},K25≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉβij)q)pqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp+qq},K26≤280p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pq(n∑j=1n∑k=1(ˉqijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉqijkMgjLgkϑk)p)×(eb_∅iˉδijk1−ˉδ′ijk‖φ∗(t+♭)−φ∗(t)‖pBp+εp)},K27≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pqn∑k=1n∑j=1(MgjMgk)pεp},K28≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)pn2pqn∑j=1n∑k=1(ˉqijkMgjMgk)pεp+qq},K29≤280p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pq(n∑j=1n∑k=1(ˉνijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉνijkMgjLgkϑk)p)×(epqb_∅iˉδijk1−¯δ′ijk‖φ∗(t+♭)−φ∗(t)‖pBp+εp)},K30≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqn2pqn∑k=1n∑j=1(MgjMgk)pεp},K31≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)pn2pqn∑j=1n∑k=1(ˉνijkMgjMgk)pεp+qq},K32≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+qq[(n∑j=1(ˉμj)q)pq+(n∑j=1(|Tij|∞)q)pq]εp},K33≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)qnpqn∑j=1(|Tij|∞ˉμj)pεp+qq},K34≤140p−1maxi∈J{ϑ−pi(1b_∅i)p+1q[(n∑j=1(ˉμj)q)pq+(n∑j=1(|Sij|∞)q)pq]εp},K35≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)qnpqn∑j=1(|Sij|∞ˉμj)pεp+qq},K36≤70p−1maxi∈J{ϑ−pi(1b_∅i)p+qqεp},K37≤70p−1maxi∈J{ϑ−pi(1b_∅i)2(p+q)q|Ii|p∞εp+qq}. |
From the above estimates, it follows that
‖φ∗(t+♭)−φ∗(t)‖pBp≤P‖φ∗(t+♭)−φ∗(t)‖pBp+Qεp, | (3.12) |
where is defined in condition and
Hence, by (3.12) and , it holds that
which implies that is -almost periodic. The proof is finished.
Remark 3.1. Although we can prove that is a Banach space, we still cannot directly use the fixed point theorem to determine the existence of almost periodic solutions for (1.1). Because there are higher-order terms in system (1.1), and is not an algebra, we cannot prove that operator is a self mapping.
It is easy to prove the following stability results using the same method as the proof of Theorem 4.1 in [33] or the proof of Theorem 15 in [31].
Theorem 3.2. Assume that hold. Then system (1.1) possesses a unique Besicovitch almost periodic solution, which is globally exponentially stable, i.e., if is the Besecovitch almost periodic solution with initial value and is an arbitrary solution of system (1.1) with initial value , then there exist positive numbers and satisfying
in which .
In this section, we provide an example to demonstrate the validity of the results obtained in this paper.
Example 4.1. In system (1.1), let , and for , take the coefficients are as follows:
Then, it is easy to see that conditions and are satisfied.
Moreover, take , then through simple calculations, we obtain
Hence, and are also satisfied. Consequently, in view of Theorem 3.2, we know that system (1.1) has a unique Besicovitch almost periodic solution that is globally exponentially stable (see Figures 1–4).
Remark 4.1. Even when the system considered in Example 4.1 degenerates into a real-valued system, there are no existing results to derive the results of Example 4.1.
This article introduces a new method to establish the existence and global exponential stability of Besicovitch almost periodic solutions for Clifford-valued high-order Hopfield fuzzy NNs with operators. The methods and results of this article can be applied to study the generalized almost periodic and almost automorphic dynamics of high-order NNs.
Bing Li: Methodology, Conceptualization, Writing - review and editing; Yuan Ning: Writing - original draft, Visualization; Yongkun Li: Methodology, Conceptualization, Funding acquisition, Writing - review and editing. All authors have read and approved the final version of the manuscript for publication.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
This work was supported by the National Natural Science Foundation of China, grant number 12261098.
The authors declare no conflict of interest.
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