
This paper investigated the almost periodic dynamics of a class of Clifford-valued high-order Hopfield fuzzy neural networks with time-varying delays and D operators. Based on the Banach fixed point theorem, inequality techniques, and the definition of Besicovitch almost periodicity, we obtained the existence of Besicovitch almost periodic solutions for the considered neural network. The results of this paper are novel, and the method proposed in this paper can be used to study the existence of generalized almost periodic solutions and almost automorphic solutions to high-order neural networks. Finally, we provided a numerical example and computer simulation to demonstrate the effectiveness of the results obtained in this paper.
Citation: Bing Li, Yuan Ning, Yongkun Li. Besicovitch almost periodic solutions to Clifford-valued high-order Hopfield fuzzy neural networks with a D operator[J]. AIMS Mathematics, 2025, 10(5): 12104-12134. doi: 10.3934/math.2025549
[1] | Yuwei Cao, Bing Li . Existence and global exponential stability of compact almost automorphic solutions for Clifford-valued high-order Hopfield neutral neural networks with $ D $ operator. AIMS Mathematics, 2022, 7(4): 6182-6203. doi: 10.3934/math.2022344 |
[2] | Nina Huo, Bing Li, Yongkun Li . Global exponential stability and existence of almost periodic solutions in distribution for Clifford-valued stochastic high-order Hopfield neural networks with time-varying delays. AIMS Mathematics, 2022, 7(3): 3653-3679. doi: 10.3934/math.2022202 |
[3] | Xiaofang Meng, Yongkun Li . Pseudo almost periodic solutions for quaternion-valued high-order Hopfield neural networks with time-varying delays and leakage delays on time scales. AIMS Mathematics, 2021, 6(9): 10070-10091. doi: 10.3934/math.2021585 |
[4] | Jin Gao, Lihua Dai . Anti-periodic synchronization of quaternion-valued high-order Hopfield neural networks with delays. AIMS Mathematics, 2022, 7(8): 14051-14075. doi: 10.3934/math.2022775 |
[5] | Abdulaziz M. Alanazi, R. Sriraman, R. Gurusamy, S. Athithan, P. Vignesh, Zaid Bassfar, Adel R. Alharbi, Amer Aljaedi . System decomposition method-based global stability criteria for T-S fuzzy Clifford-valued delayed neural networks with impulses and leakage term. AIMS Mathematics, 2023, 8(7): 15166-15188. doi: 10.3934/math.2023774 |
[6] | Qian Cao, Xiaojin Guo . Anti-periodic dynamics on high-order inertial Hopfield neural networks involving time-varying delays. AIMS Mathematics, 2020, 5(6): 5402-5421. doi: 10.3934/math.2020347 |
[7] | Xiaojin Guo, Chuangxia Huang, Jinde Cao . Nonnegative periodicity on high-order proportional delayed cellular neural networks involving $ D $ operator. AIMS Mathematics, 2021, 6(3): 2228-2243. doi: 10.3934/math.2021135 |
[8] | Yongkun Li, Xiaoli Huang, Xiaohui Wang . Weyl almost periodic solutions for quaternion-valued shunting inhibitory cellular neural networks with time-varying delays. AIMS Mathematics, 2022, 7(4): 4861-4886. doi: 10.3934/math.2022271 |
[9] | Qi Shao, Yongkun Li . Almost periodic solutions for Clifford-valued stochastic shunting inhibitory cellular neural networks with mixed delays. AIMS Mathematics, 2024, 9(5): 13439-13461. doi: 10.3934/math.2024655 |
[10] | Hedi Yang . Weighted pseudo almost periodicity on neutral type CNNs involving multi-proportional delays and D operator. AIMS Mathematics, 2021, 6(2): 1865-1879. doi: 10.3934/math.2021113 |
This paper investigated the almost periodic dynamics of a class of Clifford-valued high-order Hopfield fuzzy neural networks with time-varying delays and D operators. Based on the Banach fixed point theorem, inequality techniques, and the definition of Besicovitch almost periodicity, we obtained the existence of Besicovitch almost periodic solutions for the considered neural network. The results of this paper are novel, and the method proposed in this paper can be used to study the existence of generalized almost periodic solutions and almost automorphic solutions to high-order neural networks. Finally, we provided a numerical example and computer simulation to demonstrate the effectiveness of the results obtained in this paper.
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 P is defined in condition (A4) and
Q=2p−1maxi∈J{4p−1(ˉai)pεp−1+2p−1(r1−ρ)pεp−1+70p−1(1b_∅i)p+qq(ˉaiˉb∅i)pεp−1+35p−1(1b_∅i)p+qq(ˉb∅i)p(r1−ρ)pεp−1+35p−1(1b_∅i)p+qq(ˉai)p(r1−ρ)pεp−1+35p−1(1b_∅i)2(p+q)q(ˉaiˉb∅i)p(r1−ρ)pεpq+70p−1(1b_∅i)p+qq(r1−ρ)pεp−1+35p−1(1b_∅i)2(p+q)q(ˉb∅i)p(r1−ρ)pεpq+35p−1ϑ−pi(1b_∅i)p+qqnpqn∑j=1(Lfjϑj)p×(r1−ρ)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉcij)q)pqn∑j=1(Lfjϑj)p(r1−ρ)pεpq+70p−1ϑ−pi(1b_∅i)p+1q(n∑j=1(ˉuij)q)pqn∑j=1(Lfjϑj)pεp−1+35p−1ϑ−pi(1b_∅i)p+qq×n∑j=1(Lfjϑj)pnpq(r1−ρ)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉuij)q)pqn∑j=1(Lfjϑj)p×(r1−ρ)pεpq+70p−1ϑ−pi(1b_∅i)p+qq[n∑j=1(ˉμj)p+n∑j=1|γij|p∞]εp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q(n∑j=1|γij|q∞)pqn∑j=1(ˉμj)pεpq+140p−1ϑ−pi(1b_∅i)p+qqn2pq×[n∑j=1n∑k=1(ˉθijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉθijkMgjLgkϑk)p]εp−1}+35p−1ϑ−pi(1b_∅i)p+qq×n2pqn∑k=1n∑j=1(MgjMgk)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)pn2pqn∑j=1n∑k=1(ˉθijkMgjMgk)pεpq+70p−1ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉαij)q)pqn∑j=1(Lfjϑj)pεp−1]+35p−1ϑ−pi(1b_∅i)p+qq×npqn∑j=1(Lfjϑj)p‖φ∗‖p∞εp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q(n∑j=1(ˉαij)q)pqn∑j=1(Lfjϑj)p×(r1−ρ)pεpq+700p−1ϑ−pi(1b_∅i)p+qq(n∑j=1(ˉβij)q)pqn∑j=1(Lfjϑj)pεp−1 |
+35p−1ϑ−pi(1b_∅i)p+qqnpqn∑j=1(Lfjϑj)p(r1−ρ)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q×(n∑j=1(ˉβij)q)pqn∑j=1(Lfjϑj)p‖φ∗‖p∞εpq+140p−1ϑ−pi(1b_∅i)p+qqn2pq×(n∑j=1n∑k=1(ˉqijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉqijkMgjLgkϑk)p)εp−1+35p−1ϑ−pi(1b_∅i)p+qq×n2pqn∑k=1n∑j=1(MgjMgk)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)pn2pqn∑j=1n∑k=1(ˉqijkMgjMgk)pεpq+140p−1ϑ−pi(1b_∅i)p+qqn2pq(n∑j=1n∑k=1(ˉνijkMgkLgjϑj)p+n∑j=1n∑k=1(ˉνijkMgjLgkϑk)p)εp−1+35p−1ϑ−pi(1b_∅i)p+qqn2pqn∑k=1n∑j=1(MgjMgk)pεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)pn2pq×n∑j=1n∑k=1(ˉνijkMgjMgk)pεpq+70p−1ϑ−pi(1b_∅i)p+qq[(n∑j=1(ˉμj)q)pq+(n∑j=1(|Tij|∞)q)pq]εp−1+35p−1ϑ−pi(1b_∅i)2(p+q)qnpqn∑j=1(|Tij|∞ˉμj)pεpq+70p−1ϑ−pi(1b_∅i)p+1q[(n∑j=1(ˉμj)q)pq+(n∑j=1(|Sij|∞)q)pq]εp−1+35p−1ϑ−pi(1b_∅i)2(p+q)qnpqn∑j=1(|Sij|∞ˉμj)pεpq+35p−1ϑ−pi(1b_∅i)p+qqεp−1+35p−1ϑ−pi(1b_∅i)2(p+q)q|Ii|p∞εpq}. |
Hence, by (3.12) and (A4), it holds that
‖φ∗(t+♭)−φ∗(t)‖pBp≤Qεp1−P, |
which implies that φ∗ is Bp-almost periodic. The proof is finished.
Remark 3.1. Although we can prove that W=(L∞(R,A)∩BpAP(R,A),‖⋅‖∞) 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 W is not an algebra, we cannot prove that operator T 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 (A1)−(A4) hold. Then system (1.1) possesses a unique Besicovitch almost periodic solution, which is globally exponentially stable, i.e., if ˉx is the Besecovitch almost periodic solution with initial value ˉφ and x(t) is an arbitrary solution of system (1.1) with initial value φ, then there exist positive numbers ζ>0 and N>0 satisfying
|x(t)−ˉx(t)|1≤N‖φ−ˉφ‖ϱe−ζt,t>0, |
in which ‖φ−ˉφ‖ϱ=maxi∈J{supt∈[−ϱ,0]|φi(t)−ai(t)φi(t)−(ˉφi(t)−ai(t)ˉφi(t))|1}.
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 m=3,n=2, and for i,j,k=1,2, take the coefficients are as follows:
xi(t)=e0x0i(t)+e1x1i(t)+e2x2i(t)+e3x3i(t)+e12x12i(t)+e13x13i(t)+e23x23i(t)+e123x123i(t),fj(x)=1100e0sinx12j+3250sin(x12j+x123j)e1+1168sin(x1j+x13j)e2+153sin(x2j+x123j)e3+1125e12arctanx3j+1156sin(x3j+x123j)e13+1150e23tanhx12j+140sin(x1j+x12j+x123j)e123,gj(x)=148e0sinx13j+1153sin(x12j+x23j)e1+1150e2arctanx13j+1120sin(x12j+x123j)e3+1150sin(x12j−x23j)e12+1250sin(x2j+x13j)e13+157e23sinx13j+160sin(x0j+x3j+x23j)e123,a1(t)=(0.01+0.004sint)e0+(0.01+0.001sin√6t)e1+(0.01+0.001cos√3t)e2+(0.01+0.002sin√5t)e3+(0.01+0.003sint)e12+(0.01+0.002cost)e13+(0.01+0.002cos√2t)e23+(0.01+0.002sin√2t)e123,a2(t)=(0.01+0.002sint)e0+(0.01+0.002cos3t)e1+(0.01+0.001sin√2t)e2+(0.01+0.001sin√7t)e3+(0.01+0.001sin√5t)e12+(0.01+0.002cost)e13+(0.01+0.002cos√5t)e23+(0.01+0.002sin√3t)e123,b1(t)=(10+0.05sint)e0+(0.2+0.01cos√2t)e1+(0.2+0.02sint)e2+(0.2+0.01sin√3t)e3+(0.2+0.06sin3t)e12+(0.2+0.05sin2t)e13+(0.2+0.01sint)e23+(0.2+0.01cos√3t)e123,b2(t)=(0.2+0.01cos√3t)e0+(0.2+0.02sint)e1+(0.2+0.07cost)e2+(0.2+0.05cos√5t)e3+(10+0.05sin√5t)e12+(0.2+0.02cos√5t)e13+(0.2+0.01sint)e23+(0.2+0.01sin7t)e123,c11(t)=0.01e0sin2t+0.02e3sin2t+0.02e23cos√2t+0.03e123cos11t,c12(t)=0.01e0sin√5t+0.02e2cos23t+0.01e3sin5t+0.03e12sin√3t,c21(t)=0.01e0sin6t+0.02e3cos√2t+0.03e23cos√3t+0.03e123cos22t,c22(t)=0.01e0sin27t+0.04e2cos6t+0.04e3sin√5t+0.03e12cos7t,u11(t)=0.02e0sin4t+0.01e3cos√2t+0.04e23cos√3t+0.03e123sin22t,u12(t)=0.02e0cos9t+0.03e2cos23t+0.04e3sin5t+0.01e12sin3t,u21(t)=0.02e0sin3t+0.03e3cos√3t+0.01e23cos√3t+0.02e123sin27t,u22(t)=0.02e0cost+0.03e2sin25t+0.03e3sin3t+0.04e12cos2t,α11(t)=0.01e3sin3t+0.04e12cos5t+0.02e13cos√5t+0.03e123sin23t,α12(t)=0.01e2sin√3t+0.02e3sin4t+0.03e12sin7t+0.01e123cos25t,α21(t)=0.03e3cos4t+0.01e12sin√5t+0.03e23cos4t+0.01e123cos25t,α22(t)=0.01e0cos√5t+0.04e3sin3t+0.03e12sin23t+0.02e123cos4t,β11(t)=0.01e0cos5t+0.02e1sin3t+0.01e2sin√7t+0.03e123cos3t,β12(t)=0.03e0sin7t+0.02e1sint+0.03e2sin√3t+0.02e23sin3t,β21(t)=0.03e0cos7t+0.02e1sin√5t+0.04e2sin√6t+0.01e123sin5t,β22(t)=0.03e0cos2t+0.02e1cos3t+0.04e2cos√2t+0.02e23cos3t,θ111(t)=0.03e0sin√2t+0.02e1cos√5t+0.01e2sin√7t+0.02e12cos2t,θ112(t)=0.04e0cos√5t+0.02e1sin3t+0.03e2sin√3t+0.03e13cos√3t,θ121(t)=0.02e0sin√3t+0.02e2cos3t+0.04e12sin√6t+0.01e23cos3t,θ122(t)=0.03e0sin√5t+0.04e2cos5t+0.03e12sin√5t+0.02e23cos4t,θ211(t)=0.03e0sin3t+0.03e1cost+0.01e2cos4t+0.01e12sin5t,θ212(t)=0.04e0cos3t+0.02e1sint+0.01e2cos3t+0.01e13sin3t,θ221(t)=0.03e0sin4t+0.03e2cos√2t+0.02e12sin5t+0.03e23cos3t,θ222(t)=0.01e0sin4t+0.01e2cos3t+0.01e12sin4t+0.04e123cos2t,q111(t)=0.06e0sin5t+0.04e1cos6t+0.03e12sin√3t+0.03e23sin22t,q112(t)=0.05e0sin2t+0.02e1cos√2t+0.04e2sin3t+0.02e23cos3t,q121(t)=0.02e0cos4t+0.02e1cos23t+0.05e2sin4t+0.03e23cos4t,q122(t)=0.05e0sin4t+0.03e1cos√3t+0.03e12cos2t+0.04e23sin3t,q211(t)=0.01e0cos√5t+0.02e1sin3t+0.04e12cos√3t+0.02e23sint,q212(t)=0.01e0cos4t+0.06e1cos√2t+0.03e12sin5t+0.04e23cos2t,q221(t)=0.01e0cos3t+0.02e1sint+0.02e2cos√3t+0.01e23sin2t,q222(t)=0.01e0cos9t+0.05e1cos23t+0.03e12sint+0.05e23cost,ν111(t)=0.02e0sin3t+0.03e1cos√3t+0.01e2cos5t+0.01e12sin4t,ν112(t)=0.02e0cost+0.03e1sin25t+0.02e12cos3t+0.03e23sin2t,ν121(t)=0.05e0sin3t+0.04e2sin3t+0.03e12cos2t+0.02e23sin3t,ν122(t)=0.03e0cos2t+0.04e2cos√3t+0.05e12sin√2t+0.04e23cos√3t,ν211(t)=0.03e0sin7t+0.04e1sin3t+0.02e2cos√3t+0.03e12sin2t,ν212(t)=0.05e0cos5t+0.02e2cos4t+0.03e12sin7t+0.04e23cost,ν221(t)=0.02e0sin3t+0.03e2cos2t+0.04e12sint+0.01e23cos2t,ν222(t)=0.03e0sin6t+0.03e2cost+0.01e12sin2t+0.04e23cos3t,I1(t)=0.32e0(sin√5t+11+t2)+0.5e1cos√2t+0.36e2sin√3t+0.23e3cos√3t+0.49e12sin√2t+0.25e13cos√5t+0.42e23cos√5t+0.15e123(sin√3t+e−|t|),I2(t)=0.25e0cos√3t+0.42e1(sin√2t+e−|t|)+0.28e2sin√3t+0.45e3cos√3t+0.32e12(cos√2t+11+t2)+0.46e13sin√3t+0.15e23sin√5t+0.26e123cos√3t,γij(t)=0.07e0cos2t+0.03e1sin2t+0.04e2(sin2t+11+t2)+0.06e3cost+0.08e12(sint+e−|t|)+0.02e13cost+0.05e23sin2t+0.04e123cost,μj(t)=0.2e0sin√2t+0.3e1sin√3t+0.4e2sin√2t+0.6e3cos√2t+0.8e12cos√3t+0.3e13cos√5t+0.4e23sin√3t+0.2e123cos√6t,Tij(t)=0.006e0sint+0.004e1sint+0.003e2(sint+11+t2)+0.001e3cost+0.002e12sint+0.003e13(cost+e−|t|)+0.002e23cost+0.005e123sint,Sij(t)=0.002e0cost+0.003e1sint+0.001e2cost+0.001e3(sint+12+t2)+0.003e12(sint+e−|t+1|)+0.002e13cost+0.001e23sint+0.002e123cost,σij(t)=1−0.3sint,ηij(t)=1−0.8cos3t,δijk(t)=1−0.6sin2t,τ1(t)=1−0.1sint,τ2(t)=1−0.3cost. |
Then, it is easy to see that conditions (A1) and (A2) are satisfied.
Moreover, take ϑ1=ϑ2=1,p=3,q=32, then through simple calculations, we obtain
ˉa1=0.014,ˉa2=0.012,ˉb∅1=10.05,ˉbc1=0.26,b_∅1=9.95,ˉb∅2=10.05,ˉbc2=0.27,b_∅2=9.95,ˉc11=0.03,ˉc12=0.03,ˉc21=0.03,ˉc22=0.04,ˉu11=0.04,ˉu12=0.04,ˉu21=0.03,ˉu22=0.04,ˉα11=0.04,ˉα12=0.03,ˉα21=0.03,ˉα22=0.04,ˉβ11=0.03,ˉβ12=0.03,ˉβ21=0.04,ˉβ22=0.04,ˉθ111=0.03,ˉθ112=0.04,ˉθ121=0.04,ˉθ122=0.04,ˉθ211=0.03,ˉθ212=0.04,ˉθ221=0.03,ˉθ222=0.04,ˉq111=0.06,ˉq112=0.05,ˉq121=0.05,ˉq122=0.05,ˉq211=0.04,ˉq212=0.06,ˉq221=0.02,ˉq222=0.05,ˉν111=0.03,ˉν112=0.03,ˉν121=0.05,ˉν122=0.05,ˉν211=0.04,ˉν212=0.05,ˉν221=0.04,ˉν222=0.04,ˉτi=ˉτ′i=0.1,ˉσij=ˉσ′ij=0.3,ˉηij=ˉη′ij=0.8,ˉδijk=ˉδ′ijk=0.6,Lf1=Lf2=140,Lg1=Lg2=148,Mg1=Mg2=148,ρ≈0.054972<1,P≈0.518973<1. |
Hence, (A3) and (A4) 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 D 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.
[1] |
C. Huang, X. Long, J. Cao, Stability of antiperiodic recurrent neural networks with multiproportional delays, Math. Methods Appl. Sci., 43 (2020), 6093–6102. https://doi.org/10.1002/mma.6350 doi: 10.1002/mma.6350
![]() |
[2] |
G. Tan, Z. Wang, Stability analysis of recurrent neural networks with time-varying delay based on a flexible negative-determination quadratic function method, IEEE Trans. Neural Netw. Learn. Syst., 36 (2025), 1933–1938. https://doi.org/10.1109/TNNLS.2023.3327318 doi: 10.1109/TNNLS.2023.3327318
![]() |
[3] |
W. Wang, W. Zeng, W. Chen, Global exponential stability of periodic solutions for inertial delayed BAM neural networks, Commun. Nonlinear Sci. Numer. Simulat., 145 (2025), 108728. https://doi.org/10.1016/j.cnsns.2025.108728 doi: 10.1016/j.cnsns.2025.108728
![]() |
[4] |
S. Chang, Y. Wang, X. Zhang, X. Wang, A new method to study global exponential stability of inertial neural networks with multiple time-varying transmission delays, Math. Comput. Simul., 211 (2023), 329–340. https://doi.org/10.1016/j.matcom.2023.04.008 doi: 10.1016/j.matcom.2023.04.008
![]() |
[5] |
W. Wang, J. Wu, W. Chen, The characteristics method to study global exponential stability of delayed inertial neural networks, Math. Comput. Simul., 232 (2025), 91–101. https://doi.org/10.1016/j.matcom.2024.12.021 doi: 10.1016/j.matcom.2024.12.021
![]() |
[6] |
Q. Wan, Z. Yan, F. Li, J. Liu, S. Chen, Multistable dynamics in a Hopfield neural network under electromagnetic radiation and dual bias currents, Nonlinear Dyn., 109 (2022), 2085–2101. https://doi.org/10.1007/s11071-022-07544-x doi: 10.1007/s11071-022-07544-x
![]() |
[7] |
M. Akhmet, M. Tleubergenova, A. Zhamanshin, Cohen-Grossberg neural networks with unpredictable and Poisson stable dynamics, Chaos Soliton. Fract., 178 (2024), 114307. https://doi.org/10.1016/j.chaos.2023.114307 doi: 10.1016/j.chaos.2023.114307
![]() |
[8] |
A. M. Alimi, C. Aouiti, F. Chérif, F. Dridi, M. S. M'hamdi, Dynamics and oscillations of generalized high-order Hopfield neural networks with mixed delays, Neurocomputing, 321 (2018), 274–295. https://doi.org/10.1016/j.neucom.2018.01.061 doi: 10.1016/j.neucom.2018.01.061
![]() |
[9] |
C. Aouiti, E. A. Assali, Stability analysis for a class of impulsive high-order hopfield neural networks with leakage time-varying delays, Neural Comput. Appl., 31 (2019), 7781–7803. https://doi.org/10.1007/s00521-018-3585-z doi: 10.1007/s00521-018-3585-z
![]() |
[10] |
Y. Li, J. Xiang, B. Li, Almost periodic solutions of quaternion-valued neutral type high-order hopfield neural networks with state-dependent delays and leakage delays, Appl. Intell., 50 (2020), 2067–2078. https://doi.org/10.1007/s10489-020-01634-2 doi: 10.1007/s10489-020-01634-2
![]() |
[11] |
B. Li, Y. Cao, Y. Li, The dynamics of octonion-valued neutral type high-order Hopfield neural networks with D operator, J. Intell. Fuzzy Syst., 44 (2023), 9599–9613. https://doi.org/10.3233/JIFS-223766 doi: 10.3233/JIFS-223766
![]() |
[12] |
Y. Wang, X. Yang, X. Chen, C. Liu, Positivity and semi-global polynomial stability of high-order Cohen-Grossberg BAM neural networks with multiple proportional delays, Inform. Sci., 689 (2025), 121512. https://doi.org/10.1016/j.ins.2024.121512 doi: 10.1016/j.ins.2024.121512
![]() |
[13] |
S. K. Panda, A. M. Nagy, V. Vijayakumar, B. Hazarika, Stability analysis for complex-valued neural networks with fractional order, Chaos Soliton. Fract., 175 (2023), 114045. https://doi.org/10.1016/j.chaos.2023.114045 doi: 10.1016/j.chaos.2023.114045
![]() |
[14] |
W. Yang, J. Huang, X. He, S. Wen, Fixed-time synchronization of complex-valued neural networks for image protection and 3D point cloud information protection, Neural Netw., 172 (2024), 106089. https://doi.org/10.1016/j.neunet.2023.12.043 doi: 10.1016/j.neunet.2023.12.043
![]() |
[15] |
Y. Chen, Y. Xue, X. Yang, X. Zhang, A direct analysis method to Lagrangian global exponential stability for quaternion memristive neural networks with mixed delays, Appl. Math. Comput., 439 (2023), 127633. https://doi.org/10.1016/j.amc.2022.127633 doi: 10.1016/j.amc.2022.127633
![]() |
[16] |
X. Wu, Z. Tu, T. Peng, D. Wang, Global attractive set for quaternion-valued neural networks with neutral items, Sci. Rep. UK, 14 (2024), 17975. https://doi.org/10.1038/s41598-024-68763-3 doi: 10.1038/s41598-024-68763-3
![]() |
[17] |
S. Baluni, I. Sehgal, V. K. Yadav, S. Das, Exponential synchronization of a class of quaternion-valued neural network with time-varying delays: A Matrix Measure Approach, Chaos Soliton. Fract., 182 (2024), 114794. https://doi.org/10.1016/j.chaos.2024.114794 doi: 10.1016/j.chaos.2024.114794
![]() |
[18] |
Y. Wu, Z. Tu, N. Dai, L. Wang, N. Hu, T. Peng, Stability analysis of quaternion-valued neutral neural networks with generalized activation functions, Cognitive Comput., 16 (2024), 392–403. https://doi.org/10.1007/s12559-023-10212-w doi: 10.1007/s12559-023-10212-w
![]() |
[19] |
Q. Shao, Y. Li, Almost periodic solutions for Clifford-valued stochastic shunting inhibitory cellular neural networks with mixed delays, AIMS Math., 9 (2024), 13439–13461. https://doi.org/10.3934/math.2024655 doi: 10.3934/math.2024655
![]() |
[20] |
N. Zhao, Y. Qiao, Stability analysis of Clifford-valued memristor-based neural networks with impulsive disturbances and its application to image encryption, Appl. Math. Comput., 475 (2024), 128710. https://doi.org/10.1016/j.amc.2024.128710 doi: 10.1016/j.amc.2024.128710
![]() |
[21] |
J. Li, H. Zhao, Y. Zhang, S. Zhu, Y. Zhang, Multistability of equilibrium points and periodic solutions for Clifford-valued memristive Cohen-Grossberg neural networks with mixed delays, Math. Methods Appl. Sci., 47 (2024), 2679–2701. https://doi.org/10.1002/mma.9772 doi: 10.1002/mma.9772
![]() |
[22] |
N. Huo, Y. Li, Pseudo almost periodic solution of fractional-order Clifford-valued high-order hopfield neural networks, J. Appl. Anal. Comput., 14 (2024), 2488–2504. https://www.jaac-online.com/article/doi/10.11948/20220447 doi: 10.11948/20220447
![]() |
[23] |
Y. Li, N. Huo, B. Li, On μ-pseudo almost periodic solutions for Clifford-valued neutral type neural networks with delays in the leakage term, IEEE Trans. Neural Netw. Learn. Syst., 32 (2021), 1365–1374. DOI: 10.1109/TNNLS.2020.2984655 doi: 10.1109/TNNLS.2020.2984655
![]() |
[24] |
C. A. Popa, Global exponential stability of neutral-type octonion-valued neural networks with time-varying delays, Neurocomputing, 309 (2018), 117–133. https://doi.org/10.1016/j.neucom.2018.05.004 doi: 10.1016/j.neucom.2018.05.004
![]() |
[25] |
N. Huo, Y. Li, B-almost periodic solutions in finite-dimensional distributions for octonion-valued stochastic shunting inhibitory cellular neural networks, Math. Methods Appl. Sci., 47 (2024), 5136–5160. https://doi.org/10.1002/mma.9858 doi: 10.1002/mma.9858
![]() |
[26] |
C. A. Popa, Stability and synchronization of octonion-valued neural networks with leakage and mixed delays on time scales, Comput. Appl. Math., 43 (2024), 300. https://doi.org/10.1007/s40314-024-02820-5 doi: 10.1007/s40314-024-02820-5
![]() |
[27] | S. Buchholz, A Theory of Neural Computation with Clifford Algebras, PhD thesis, University of Kiel, 2005. https://macau.uni-kiel.de/receive/macau_mods_00001896 |
[28] |
S. Buchholz, G. Sommer, On Clifford neurons and Clifford multi-layer perceptrons, Neural Netw., 21 (2008), 925–935. https://doi.org/10.1016/j.neunet.2008.03.004 doi: 10.1016/j.neunet.2008.03.004
![]() |
[29] |
E. Hitzer, T. Nitta, Y. Kuroe, Applications of Clifford's geometric algebra, Adv. Appl. Clifford Al., 23 (2013), 377–404. https://doi.org/10.1007/s00006-013-0378-4 doi: 10.1007/s00006-013-0378-4
![]() |
[30] |
S. Breuils, K. Tachibana, E. Hitzer, New applications of Clifford's geometric algebra, Adv. Appl. Clifford Al., 32 (2022), 17. https://doi.org/10.1007/s00006-021-01196-7 doi: 10.1007/s00006-021-01196-7
![]() |
[31] |
M. Ayachi, Measure-pseudo almost periodic dynamical behaviors for BAM neural networks with D operator and hybrid time-varying delays, Neurocomputing, 486 (2022), 160–173. https://doi.org/10.1016/j.neucom.2021.11.020 doi: 10.1016/j.neucom.2021.11.020
![]() |
[32] |
F. Kong, Q. Zhu, Finite-time stabilization of discontinuous fuzzy neutral-type neural networks with D operator and multiple time-varying delays, Fuzzy Sets Syst., 449 (2022), 32–55. https://doi.org/10.1016/j.fss.2022.02.006 doi: 10.1016/j.fss.2022.02.006
![]() |
[33] |
B. Li, Y. Cao, Y. Li, Almost periodic oscillation in distribution for octonion-valued neutral-type stochastic recurrent neural networks with D operator, Nonlinear Dyn., 111 (2023), 11371–11388. https://doi.org/10.1007/s11071-023-08411-z doi: 10.1007/s11071-023-08411-z
![]() |
[34] | C. Huang, B. Liu, H. Yang, J. Cao, Positive almost periodicity on SICNNs incorporating mixed delays and D operator, Nonlinear Anal. Model., 27 (2022), 719–739. https://orcid.org/0000-0002-0732-226X |
[35] |
S. Subramaniam, P. Mani, Sampled-data synchronization for fuzzy inertial cellular neural networks and its application in secure communication, Neural Netw., 180 (2024), 106671. https://doi.org/10.1016/j.neunet.2024.106671 doi: 10.1016/j.neunet.2024.106671
![]() |
[36] |
P. V. de C. Souza, Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature, Appl. Soft Comput., 92 (2020), 106275. https://doi.org/10.1016/j.asoc.2020.106275 doi: 10.1016/j.asoc.2020.106275
![]() |
[37] |
C. H. Lee, C. C. Teng, Identification and control of dynamic systems using recurrent fuzzy neural networks, IEEE Trans. Fuzzy Syst., 8 (2000), 349–366. https://doi.org/10.1109/91.868943 doi: 10.1109/91.868943
![]() |
[38] |
Y. Wang, H. Ishibuchi, M. J. Er, J. Zhu, Unsupervised multilayer fuzzy neural networks for image clustering, Inform. Sci., 622 (2023), 682–709. https://doi.org/10.1016/j.ins.2022.11.149 doi: 10.1016/j.ins.2022.11.149
![]() |
[39] |
M. Alateeq, W. Pedrycz, Logic-oriented fuzzy neural networks: A survey, Expert Syst. Appl., 257 (2024), 125120. https://doi.org/10.1016/j.eswa.2024.125120 doi: 10.1016/j.eswa.2024.125120
![]() |
[40] | C. Corduneanu, Almost periodic oscillations and waves, New York: Springer, 2009. https://doi.org/10.1007/978-0-387-09819-7 |
[41] | F. Brackx, R. Delanghe, F. Sommen, Clifford analysis, Boston: Pitman Books Limited, 1982. Available from: http://hdl.handle.net/1854/LU-697713 |
[42] |
S. Shen, Y. Li, Sp-Almost periodic solutions of Clifford-valued fuzzy cellular neural networks with time-varying delays, Neural Process. Lett., 51 (2020), 1749–1769. https://doi.org/10.1007/s11063-019-10176-9 doi: 10.1007/s11063-019-10176-9
![]() |
[43] |
B. Li, Y. Zhang, Y. Li, Besicovitch-like almost periodic solutions of Clifford-valued fuzzy cellular neural networks with time-varying delays, Franklin Open, 2 (2023), 100011. https://doi.org/10.1016/j.fraope.2023.100011 doi: 10.1016/j.fraope.2023.100011
![]() |
[44] |
X. Huang, Y. Li, Weyl almost periodic solutions of octonion-valued high-order fuzzy neural networks with delays, Comp. Appl. Math., 42 (2023), 155. https://doi.org/10.1007/s40314-023-02294-x doi: 10.1007/s40314-023-02294-x
![]() |