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Research article

Asymptotic stability for quaternion-valued BAM neural networks via a contradictory method and two Lyapunov functionals

  • We explore the existence and asymptotic stability of equilibrium point for a class of quaternion-valued BAM neural networks with time-varying delays. Firstly, by employing Homeomorphism theorem and a contradictory method with novel analysis skills, a criterion ensuring the existence of equilibrium point of the considered quaternion-valued BAM neural networks is acquired. Secondly, by constructing two Lyapunov functionals, a criterion assuring the global asymptotic stability of equilibrium point for above discussed quaternion-valued BAM is presented. Applying a contradictory method to study the equilibrium point and applying two Lyapunov functionals to study stability of equilibrium point are completely new methods.

    Citation: Ailing Li, Mengting Lv, Yifang Yan. Asymptotic stability for quaternion-valued BAM neural networks via a contradictory method and two Lyapunov functionals[J]. AIMS Mathematics, 2022, 7(5): 8206-8223. doi: 10.3934/math.2022457

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  • We explore the existence and asymptotic stability of equilibrium point for a class of quaternion-valued BAM neural networks with time-varying delays. Firstly, by employing Homeomorphism theorem and a contradictory method with novel analysis skills, a criterion ensuring the existence of equilibrium point of the considered quaternion-valued BAM neural networks is acquired. Secondly, by constructing two Lyapunov functionals, a criterion assuring the global asymptotic stability of equilibrium point for above discussed quaternion-valued BAM is presented. Applying a contradictory method to study the equilibrium point and applying two Lyapunov functionals to study stability of equilibrium point are completely new methods.



    Riemann-Liouville fractional integral given by

    Iαa+ξ()=1Γ(α)χa(χ)α1ξ()dt.

    Many different concepts of fractional derivative maybe found in [9,10,11]. In [12] studied a conformable derivative:

    αf()=limϵ0f(+ϵ1α)f()ϵ.

    The time scale conformable derivatives was introduced by Benkhettou et al. [17].

    Further, in recent years, numerous mathematicians claimed that non-integer order derivatives and integrals are well suited to describing the properties of many actual materials, such as polymers. Fractional derivatives are a wonderful tool for describing memory and learning. a variety of materials and procedures inherited properties is one of the most significant benefits of fractional ownership. For more concepts and definition on time scales see [13,14,15,16,17,18,19,33,34,35].

    Continuous version of Steffensen's inequality [7] is written as: For 0g()1 on [a,b]. Then

    bbλf()dtbaf()g()dta+λaf()dt, (1.1)

    where λ=bag()dt.

    Supposing f is nondecreasing gets the reverse of (1.1).

    Also, the discrete inequality of Steffensen [6] is: For λ2n=1g()λ1. Then

    n=nλ2+1f()n=1f()g()λ1=1f(). (1.2)

    Recently, a large number of dynamic inequalities on time scales have been studied by a small number of writers who were inspired by a few applications (see [1,2,3,4,8,28,29,30,31,32,36,37,40,41,42,44,48,49,50,51,52,53]).

    In [5] Jakšetić et al. proved that, if ˆμ([c,d])=[a,b]g()dˆμ(), where [c,d][a,b]. Then

    [a,b]f()g()dˆμ()[c,d]f()g()dˆμ()+[a,c](f()f(d))g()dˆμ(),

    and

    [c,d]f()dˆμ()[d,b](f(c)f())g()dˆμ()[a,b]f()g()dˆμ().

    Anderson, in [3], studied the inequality:

    bbλϕ()baϕ()ψ()a+λaϕ(), (1.3)

    In [47] the authors have proved, for

    m+λ1mζ()d=kmζ()g()d,

    and

    nnλ2ζ()d=nkζ()g()d.

    If there exists a constant A such that r()/ζ()At is monotonic on the intervals [m,k], [k,n], and

    nmtq()g()d=m+λ1mtq()d+nnλ2tq()d,

    then

    nmr()g()dm+λ1mr()d+nnλ2r()d.

    In particularly, Anderson [3] proved

    nnλr()nmr()g()m+λmr().

    where m,nTκ with m<n, r, g:[m,n]TR are -integrable functions such that r is of one sign and nonincreasing and 0g()1 on [m,n]T and λ=nmg(), nλ,m+λT.

    We prove the next two needed results:

    Theorem 1.1. Assume q>0 with 0g()ζ() [m,n]T and λ is given from nmg()Δα=m+λmζ()Δα, then

    nmr()g()Δαm+λmr()ζ()Δα. (1.4)

    Also, provided with 0g()ζ() and nnλζ()Δα=nmg()Δα, we have

    nnλr()ζ()Δαnmr()g()Δα. (1.5)

    We get the reverse inequalities of (1.4) and (1.5) when assuming r/ζ is nondecreasing.

    Theorem 1.2. Assume ψ is integrable on time scales interval [m,n], with ζ()ψ()g()ψ()0[m,n]T and m+λmζ()Δα=nmg()Δα=nnλζ()Δα and g, r and ζ are Δα-integrable functions, ζ()g()0, we have

    nnλr()ζ()Δα+nm|(r()r(nλ))ψ()|Δαnmr()g()Δαm+λmr()ζ()Δαnm|(r()r(m+λ))ψ()|Δα, (1.6)

    and

    nnλr()ζ()Δαnnλ[r()ζ()(r()r(nλ))][ζ()g()]Δαnmr()g()Δαm+λm[r()ζ()(r()r(m+λ))][ζ()g()]Δαm+λmr()ζ()Δα. (1.7)

    Proof. The proof techniques of Theorems 1.6 and 1.7 are like to that in [4] and is removed.

    Several authors proved conformable Hardy's inequality [20,21], conformable Hermite-Hadamard's inequality [22,23,24], conformable inequality of Opial's [26,27] and conformable inequality of Steffensen's [25]. In [45] Anderson proved the followong results:

    Theorem 1.3. [45] Suppose α(0,1] and r1, r2R such that 0r1r2. Suppose :[r1,r2][0,) and Γ:[r1,r2][0,1] are α-fractional integrable functions on [r1,r2] with Π is decreasing, we get

    r2r2Π(ζ)dαζr2r1Π(ζ)Γ(ζ)dαζr1+r1Π(ζ)dαζ,

    where =α(r2r1)rα2rα1r2r1Γ(ζ)dαζ[0,r2r1].

    In [46] the authors gave an extension for Theorem 1.8:

    Theorem 1.4. Assume α(0,1] and r1, r2R such that 0r1r2. Suppose ,Γ,Σ:[r1,r2][0,) are integrable on [r1,r2] with the decreasing function Π and 0ΓΣ, we get

    r2r2Σ(ζ)Π(ζ)dαζr2r1Π(ζ)Γ(ζ)dαζr1+r1Σ(ζ)Π(ζ)dαζ,

    where =(r2r1)r2r1Σ(ζ)dαζr2r1Γ(ζ)dαζ[0,r2r1].

    In this paper, we prove and explore several novel speculations of the Steffensen inequality obtained in [47] through the conformable integral containing time scale concept. We furthermore recover certain known results as special cases of our results.

    Lemma 2.1. Assume ζ>0 is rd-continuous function on [m,n]T, g, r be rd-continuous on [m,n]T such that r/ζ nonincreasing function and 0g()1 [m,n]T. Then

    (Λ1)

    nmr()g()Δαm+λmr()Δα, (2.1)

    where λ is given by

    nmζ()g()Δα=m+λmζ()Δα.

    (Λ2)

    nnλr()Δαnmr()g()Δα, (2.2)

    such that

    nnλζ()Δα=nmζ()g()Δα.

    (2.1) and (2.2) are reversed when r/ζ is nondecreasing.

    Proof. Putting g()ζ()g() and r()r()/ζ() in (1.4), (1.5) to get (Λ1) and (Λ2) simultaneously.

    Lemma 2.2. Under the same hypotheses of Lemma 2.1. with ψ be integrable functions on [m,n]T and 0ψ()g()1ψ() for all [m,n]T. Then

    nnλr()Δα+nm|(r()ζ()r(nλ)ζ(nλ))ζ()ψ()|Δαnmr()g()Δαm+λmr()Δαnm|(r()ζ()r(m+λ)ζ(m+λ))ζ()ψ()|Δα,

    where λ is obtained from

    m+λmh()Δα=nmζ()g()Δα=nnλζ()Δα.

    Proof. Putting g()ζ()g(), r()r()/h() and ψ()ζ()ψ() in (1.6).

    Lemma 2.3. Under the same conditions of Lemma 2.1. Then

    nnλr()Δαnnλ(r()[r()ζ()r(nλ)ζ(nλ)]ζ()[1g()])Δαnmr()g()Δαm+λm(r()[r()ζ()r(a+λ)ζ(m+λ)]ζ()[1g()])Δαm+λmr()Δα,

    where λ is obtained from

    m+λmζ()Δα=nmg()Δα=nnλζ()Δα.

    Proof. Taking g()ζ()g() and r()r()/ζ() in (1.7).

    Theorem 2.1. Under the same conditions of Lemma 2.3 such that k(m,n) and λ1, λ2 are given from

    (Λ3)

    m+λ1mζ()Δα=kmζ()g()Δα,
    nnλ2ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δα, (2.3)

    then

    nmrσ()g()Δαm+λ1mrσ()Δα+nnλ2rσ()Δα. (2.4)

    (2.4) is reversed if rσ/ζAHk2[m,n] and (2.3).

    (Λ4)

    kkλ1ζ()Δα=kmζ()g()Δα,
    k+λ2kζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()ζ()Δα, (2.5)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()Δα. (2.6)

    If rσ/ζAHk2[m,n] and (2.5) satisfied, then we reverse (2.6).

    (Λ5) If λ1, λ2 be the same as in (Λ3) and rσ/ζAHk1[m,n] so that

    nmϕ()ζ()g()Δα=m+λ1m(ϕ()ζ()[ϕ()mλ1]ζ()[1g()])Δα+nnλ2(ϕ()ζ()[ϕ()n+λ2]ζ()[1g()])Δα, (2.7)

    then

    nmrσ()g()Δαm+λ1m(rσ()|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()[1g()])Δα+nnλ2(rσ()|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()[1g()])Δα. (2.8)

    If rσ/ζAHk2[m,n] and (2.7) satisfied, the inequality in (2.8) is reversed.

    (Λ6) If λ1, λ2 be defined as in (Λ4) and rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=kkλ1(ϕ()ζ()[ϕ()k+λ1]ζ()[1g()])Δα=m+λ1m(ϕ()ζ()[ϕ()k+λ2]ζ()[1g()])Δα, (2.9)

    then

    nmrσ()g()Δαkkλ1(rσ()[rσ()ζ()rσ(kλ1)ζ(kλ1)]ζ()[1g()])Δα+k+λ2k(rσ()[rσ()ζ()rσ(k+λ2)ζ(k+λ2)]ζ()[1g()])Δα. (2.10)

    If rσ/ζAHk2[m,n] and (2.9) satisfied, we reverse (2.10).

    Proof. (Λ3) Consider rσ/ζAHk1[m,n], and R1()=rσ()Aϕ()ζ(), since A is given in Definition 2.1. Since R1/ζ:[m,k]TR, using Lemma 2.1(Λ1), we deduce

    0m+λ1mR1()ΔαkmR1()g()Δα=m+λ1mrσ()Δαkmrσ()g()ΔαA(m+λ1mϕ()ζ()Δαkmϕ()ζ()g()Δα). (2.11)

    As R1/ζ:[k,n]TR is nondecreasing, using Lemma 2.1(Λ2), we obtain

    0nkR1()g()Δαnnλ2R1()Δα=nkrσ()g()Δαnnλ2rσ()ΔαA(nkϕ()ζ()g()Δαnnλ2ϕ()ζ()Δα). (2.12)

    (2.11) and (2.12) imply that

    m+λ1mrσ()Δα+nnλ2rσ()Δαnmrσ()g()ΔαA(m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δαnmϕ()ζ()g()Δα)

    Hence, if (2.3) is hold, then (2.4) holds. For rσ/ζAHk2[m,n], we get the some steps.

    (Λ4) Let rσ/ζAHk1[m,n], also R1(x)=rσ(x)Aϕ(x)ζ(x), where A as in Definition 2.1. R1/ζ:[m,k]TR is nonincreasing, so from Lemma 2.1(Λ1) we obtain

    0kmrσ()g()Δαkkλ1rσ()ΔαA(kmϕ()h()g()Δαkcλ1ϕ()ζ()Δα). (2.13)

    Using Lemma 2.1(Λ1) we have

    0k+λ2krσ()Δαnkrσ()g()ΔαA(k+λ2kϕ()ζ()Δαnkϕ()ζ()g()Δα). (2.14)

    Thus, from (2.13), (2.14), we get

    nmrσ()g()Δαk+λ2kλ1rσ()ΔαA(nmϕ()ζ()g()Δαk+λ2kλ1ϕ()ζ()Δα)

    Therefore, if nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()ζ()Δα is satisfied, then (2.8) holds. Follow the same steps for rσ/ζAHk2[m,n].

    Using Lemma 2.3 and repeat the steps of Theorem 2.1(Λ3) and Theorem 2.1(Λ4) in the proof of (Λ5) and (Λ6) respectively.

    Corollary 2.1. The inequalities (2.4), (2.6), (2.8) and (2.10) of Theorem 2.1 letting T=R takes

    (i)nmfσ()g()dαm+λ1mrσ()dα+nnλ2rσ()dα. (2.15)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()dα. (2.16)
    (iii)nmrσ()g()dαm+λ1m(rσ()[rσ()ζ()rσ(m+λ1)ζ(m+λ1)]ζ()[1g()])dα+nnλ2(rσ()[rσ()ζ()rσ(nλ2)ζ(nλ2)]ζ()[1g()])dα. (2.17)
    (iv)nmrσ()g()dαkkλ1(rσ()[rσ()ζ()rσ(kλ1)ζ(kλ1)]ζ()[1g()])dα+k+λ2k(rσ()[rσ()ζ()rσ(k+λ2)ζ(k+λ2)]ζ()[1g()])dα. (2.18)

    Corollary 2.2. We get [47,Theorems 8,10,21 and 22], if we put α=1 and ϕ()= in Corollary 2.1 [(i),(ii),(iii),(iv)] simultaneously.

    Corollary 2.3. In Corollary 2.1 taking T=Z, the results (2.15)–(2.18) will be equivalent to

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)+n1=nλ2r(+1)α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)α1.
    (iii)n1=mr(+1)g()α1m+λ11=m(r(+1)[r(+1)ζ()r(a+λ1+1)ζ(m+λ1)]ζ()[1g()])α1+n1=nλ2(r(+1)[r(+1)ζ()r(nλ2+1)ζ(nλ2)]ζ()[1g()])α1.
    (iv)n1=mr(+1)g())α1k1=kλ1(r(+1)[r(+1)ζ()r(kλ1+1)ζ(kλ1)]ζ()[1g()]))α1+k+λ21=k(r(+1)[r(+1)ζ()r(k+λ2+1)ζ(k+λ2)]ζ()[1g()]))α1.

    Theorem 2.2. Under the assumptions in Lemma 2.1 with 0g()ζ() and λ1, λ2 be defined as

    (Λ7)

    m+λ1mζ()Δα=kmg()Δα,
    nnλ2ζ()Δα=nkg()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()g()Δα=m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δα, (2.19)

    then

    nmrσ()g()Δαm+λ1mrσ()ζ()Δα+nnλ2rσ()ζ()Δα. (2.20)

    (Λ8)

    kkλ1ζ()Δα=kmg()Δα,
    k+λ2kζ()Δα=nkg()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()g()Δα=k+λ2kλ1ϕ()ζ()Δα, (2.21)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()ζ()Δα. (2.22)

    If rσ/ζAHk2[m,n] and (2.19), (2.21) satisfied, we get the reverse of (2.20) and (2.22).

    Proof. By using Theorem 2.1 [(Λ3),(Λ4)] and by putting gg/h and ffh, we get the proof of (Λ7) and (Λ8).

    Corollary 2.4. In Theorem 2.2 [(Λ7),(Λ8)], assuming T=R, the following results obtains:

    (i)nmrσ()g()dαm+λ1mrσ()ζ()dα+nnλ2rσ()ζ()dα. (2.23)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()ζ()dα. (2.24)

    Corollary 2.5. In Corollary 2.4 [(i),(ii)], when we put α=1 and ϕ()= then [47,Theorems 16 and 17] gotten.

    Corollary 2.6. In (2.23) and (2.24) letting T=Z, gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)h()+n1=nλ2r(+1)h()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)ζ()α1.

    Theorem 2.3. Using the same conditions in Lemma 2.3. Letting w:[m,n]TR be integrable with 0g()w() [m,n]T and

    (Λ9)m+λ1mw()ζ()Δα=kmζ()g()Δα,
    nnλ2w()ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()w()ζ()Δα+nnλ2ϕ()w()ζ()Δα, (2.25)

    then

    nmrσ()g()Δαm+λ1mrσ()w()Δα+nnλ2rσ()w()Δα. (2.26)
    (Λ10)kkλ1w()ζ()Δα=kmζ()g()Δα,
    k+λ2kw()ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()w()ζ()Δα, (2.27)
    nmrσ()g()Δαk+λ2kλ1rσ()w()Δα. (2.28)

    The inequalities in (2.26) and (2.28) are reversible if rσ/ζAHc2[a,b] and (2.25), (2.27) hold.

    Proof. In Theorem 2.1 [(Λ3),(Λ4)], ζ changes wq, g changes g/w and r changes rw.

    Corollary 2.7. In (2.26) and (2.28). Letting T=R, we have

    (i)nmrσ()g()dαm+λ1mrσ()w()dα+nnλ2rσ()w()dα. (2.29)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()w()dα. (2.30)

    Corollary 2.8. In Corollary 2.7 [(i),(ii)], letting α=1 and ϕ()= we get [47,Theorems 18 and 19].

    Corollary 2.9. In (2.29) and (2.30), crossing T=Z, gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)w()+n1=nλ2r(+1)w()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)w()α1.

    Theorem 2.4. Using the same conditions in Lemma 2.1, and Theorem 2.1 [(Λ3),(Λ4)] with ψ:[m,n]TR be a integrable: 0ψ()g()1ψ().

    (Λ11) If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()ζ()Δαkm|ϕ()mλ1|ζ()ψ()Δα+nnλ2ϕ()ζ()Δα+nk|ϕ()n+λ2|ζ()ψ()Δα, (2.31)

    then

    nmrσ()g()Δαm+λ1mrσ()Δαkm|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()ψ()Δα+nnλ2rσ()Δα+nk|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()ψ()Δα. (2.32)

    (Λ12) If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=kkλ1ϕ()ζ()Δαkm|ϕ()k+λ1|ζ()ψ()Δα+nk|ϕ()kλ1|ζ()ψ()Δα, (2.33)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()Δα+km|rσ()ζ()rσ(kλ1)ζ(kλ1)|ζ()ψ()Δαnk|rσ()ζ()rσ(k+λ2)ζ(k+λ2)|ζ()ψ()Δα. (2.34)

    If rσ/ζAHk2[m,n] and (2.31) and (2.33) satisfied, we get the reverse of (2.32) and (2.34).

    Proof. The same steps of Theorem 2.1 [(Λ3),(Λ4)] with Lemma 2.1, R1/ζ:[m,k]TR nonincreasing, R1/ζ:[k,n]TR nondecreasing.

    Corollary 2.10. In Theorem 2.4 [(Λ11),(Λ12)], letting T=R we get:

    (i)nmrσ()g()dαm+λ1mrσ()dαkm|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()ψ()dα+nnλ2rσ()dα+nk|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()ψ()dα. (2.35)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()dα+km|rσ()ζ()rσ(kλ1)ζ(kλ1)|ζ()ψ()dαnk|rσ()ζ()rσ(k+λ2)ζ(k+λ2)|ζ()ψ()dα. (2.36)

    Corollary 2.11. In (2.35) and (2.36), we put α=1, with ϕ()= we get [47,Theorems 23 and 24].

    Corollary 2.12. Our results (2.35) and (2.36), by using T=Z gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)α1k1=m|r(+1)ζ()r(m+λ1+1)ζ(m+λ1)|ζ()ψ()ˆ+n1=nλ2r(+1)α1+n1=k|r(+1)ζ()r(nλ2+1)ζ(nλ2)|ζ()ψ()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)α1+k1=m|r(+1)ζ()r(kλ1+1)ζ(kλ1)|ζ()ψ()α1n1=k|r(+1)ζ()r(k+λ2+1)ζ(k+λ2)|h()ψ()α1.

    In this work, we explore new generalizations of the integral Steffensen inequality given in [38,39,43] by the utilization of the α-conformable derivatives and integrals, A few of these results are generalised to time scales. We also obtained the discrete and continuous case of our main results, in order to gain some fresh inequalities as specific cases.

    The authors extend their appreciation to the Research Supporting Project number (RSP-2022/167), King Saud University, Riyadh, Saudi Arabia.

    The authors declare no conflict of interest.



    [1] Y. K. Li, J. L. Qin, B. Li, Anti-periodic solutions for quaternion-valued high-order Hopfield neural networks with time-varying delays, Neural Process. Lett., 49 (2019), 1217–1237. https://doi.org/10.1007/s11063-018-9867-8 doi: 10.1007/s11063-018-9867-8
    [2] N. N. Huo, B. Li, Y. K. Li, Existence and exponential stability of anti-periodic solutions for inertial quaternion-valued high-order Hopfield neural networks with state-dependent delays, IEEE Access, 7 (2019), 60010–60019. https://doi.org/10.1109/ACCESS.2019.2915935 doi: 10.1109/ACCESS.2019.2915935
    [3] Q. K. Song, X. F. Chen, Multistability analysis of quaternion-valued neural networks with time delays, IEEE T. Neur. Net. Lear., 29 (2018), 5430–5440. https://doi.org/10.1109/TNNLS.2018.2801297 doi: 10.1109/TNNLS.2018.2801297
    [4] X. F. Chen, Q. K. Song, Z. S. Li, Z. J. Zhao, Y. R. Liu, Stability analysis of continuous-time and discrete-time quaternion-valued neural networks with linear threshold neurons, IEEE T. Neur. Net. Lear., 29 (2018), 2769–2781. https://doi.org/10.1109/TNNLS.2017.2704286 doi: 10.1109/TNNLS.2017.2704286
    [5] X. F. Chen, Z. S. Li, Q. K. Song, J. Hu, Y. S. Tan, Robust stability analysis of quaternion-valued neural networks with time delays and parameter uncertainties, Neural Networks, 91 (2017), 55–65. https://doi.org/10.1016/j.neunet.2017.04.006 doi: 10.1016/j.neunet.2017.04.006
    [6] R. X. Li, X. B. Gao, J. D. Cao, K. Zhang, Stability analysis of quaternion-valued Cohen-Grossberg-Grossberg neural networks, Math. Method. Appl. Sci., 42 (2019), 3721–3738. https://doi.org/10.1002/mma.5607 doi: 10.1002/mma.5607
    [7] X. J. Yang, C. D. Li, Q. K. Song, J. Y. Chen, J. J. Huang, Global mittag-leffler stability and synchronization analysis of fractional-order quaternion-valued neural networks with linear threshold neurons, Neural Networks, 105 (2018), 88–103. https://doi.org/10.1016/j.neunet.2018.04.015 doi: 10.1016/j.neunet.2018.04.015
    [8] Y. K. Li, J. L. Qin, B. Li, Periodic solutions for quaternion-valued fuzzy cellular neural networks with time-varying delays, Adv. Differ. Equ., 2019 (2019), 63. https://doi.org/10.1186/s13662-019-2008-5 doi: 10.1186/s13662-019-2008-5
    [9] J. W. Zhu, J. T. Sun, Stability of quaternion-valued neural networks with mixed delay, Neural Process Lett., 49 (2019), 819–833. https://doi.org/10.1007/s11063-018-9849-x doi: 10.1007/s11063-018-9849-x
    [10] Y. K. Li, J. L. Qin, Existence and global exponential stability of periodic solutions for quaternion-valued cellular neural networks with time-varying delays, Neurocomputing, 292 (2018), 91–103. https://doi.org/10.1016/j.neucom.2018.02.077 doi: 10.1016/j.neucom.2018.02.077
    [11] X. X. You, Q. K. Song, J. Liang, Y. R. Liu, F. E. Alsaadi, Global μ-stability of quaternion-valued neural networks with mixed time-varying delays, Neurocomputing, 290 (2018), 12–25. https://doi.org/10.1016/j.neucom.2018.02.030 doi: 10.1016/j.neucom.2018.02.030
    [12] X. W. Liu, Z. G. Li, Global μ-stability of quaternion-valued neural networks with unbounded and asynchronous time-varying delays, IEEE Access, 7 (2019), 9128–9141. https://doi.org/ 10.1109/ACCESS.2019.2891721 doi: 10.1109/ACCESS.2019.2891721
    [13] Z. W. Tu, Y. X. Zhao, N. Ding, Y. M. Teng, W. Zhang, Stability analysis of quaternion-valued neural networks with both discrete and distributed delays, Appl. Math. Comput., 343 (2019), 342–353. https://doi.org/10.1016/j.amc.2018.09.049 doi: 10.1016/j.amc.2018.09.049
    [14] M. C. Tan, Y. F. Liu, D. S. Xu, Multistability analysis of delayeed quaternion-valued neural networks with nonmonotonic piecewise nonlinear activation functions, Appl. Math. Comput., 341 (2019), 229–255. https://doi.org/10.1016/j.amc.2018.08.033 doi: 10.1016/j.amc.2018.08.033
    [15] R. Y. Wei, J. D. Cao, Fixed-time synchronization of quaternion-valued memristive neural networks with time delays, Neural Networks, 113 (2019), 1–10. https://doi.org/10.1016/j.neunet.2019.01.014 doi: 10.1016/j.neunet.2019.01.014
    [16] S. P. Shen, B. Li, Y. K. Li, Anti-periodic dynamics of quaternion-valued fuzzy cellular neural networks with time-varying delays on time scales, Discrete Dyn. Nat. Soc., 2018 (2018), 5290786. https://doi.org/10.1155/2018/5290786 doi: 10.1155/2018/5290786
    [17] C. A. Popa, E. Kaslik, Multistability and muitiperiodicity in impulsive hybird quaternion-valued neural networks with mixed delays, Neural Networks, 99 (2018), 1–18. https://doi.org/10.1016/j.neunet.2017.12.006 doi: 10.1016/j.neunet.2017.12.006
    [18] R. Y. Wei, J. D. Cao, Synchronization control of quaternion-valued menristive neural networks with and without event-triggered scheme, Cogn. Neyrodyn., 13 (2019), 489–502. https://doi.org/10.1007/s11571-019-09545-w doi: 10.1007/s11571-019-09545-w
    [19] H. Q. Shen, Q. K. Song, J. Liang, Z. J. Zhao, Y. R. Liu, F. E. Alsaadi, Glibal exponential stability in lagrange sense for quaternion-valued neural networks with leakage delay and mixed time-varying delays, Int. J. Syst. Sci., 50 (2019), 858–870. https://doi.org/10.1080/00207721.2019.1586001 doi: 10.1080/00207721.2019.1586001
    [20] D. H. Li, Z. Q. Zhang, X. L. Zhang, Periodic solutions of discrete-time Quaternion-valued BAM neural networks, Chaos Soliton. Fract., 138 (2020), 110144. https://doi.org/10.1016/j.chaos.2020.110144 doi: 10.1016/j.chaos.2020.110144
    [21] Q. K. Song, L. Y. Long, Z. J. Zhao, Y. R. Liu, F. E. Alsaadi, Stability criteria of quaternion-valued neutral-type delayed neural networks, Neurocomputing, 412 (2020), 287–294. https://doi.org/10.1016/j.neucom.2020.06.086 doi: 10.1016/j.neucom.2020.06.086
    [22] H. M. Wang, J. Tan, S. P. Wen, Exponential stability analysis of mixed delayed quaternion-valued neural networks via decomposed approach, IEEE Access, 8 (2020), 91501–91509. https://doi.org/10.1109/ACCESS.2020.2994554 doi: 10.1109/ACCESS.2020.2994554
    [23] U. Humphries, G. Rajchakit, P. Kaewmesri, P. Chanthorn, R. Sriraman, R. Samidurai, et al., Global stability analysis of fractional-order quaternion-valued bidirectional associative memory neural networks, Mathematics, 8 (2020), 801. https://doi.org/10.3390/math8050801 doi: 10.3390/math8050801
    [24] Z. Q. Zhang, W. B. Liu, D. M. Zhou, Global asymptotic stability to a generalized Cohen-Grossberg BAM neural networks of neutral type delays, Neural Networks, 25 (2012), 94–105. https://doi.org/10.1016/j.neunet.2011.07.006 doi: 10.1016/j.neunet.2011.07.006
    [25] Z. Q. Zhang, J. D. Cao, D. M. Zhou, Novel LMI-based conditioon on global asymptotic stability for a class of Cohen-Grossberg BAM networks with extended activation functions, IEEE T. Neur. Net. Lear., 25 (2014), 1161–1172. https://doi.org/10.1109/TNNLS.2013.2289855 doi: 10.1109/TNNLS.2013.2289855
    [26] W. L. Peng, Q. X. Wu, Z. Q. Zhang, LMI-based global exponential stability of equilibrium point for neutral delayed BAM neural networks with delays in leakage terms via new inequality technique, Neurocomputing, 199 (2016), 103–113. https://doi.org/10.1016/j.neucom.2016.03.030 doi: 10.1016/j.neucom.2016.03.030
    [27] H. L. Li, X. B. Gao, R. X. Li, Exponential stability and sampled-data synchronization of delayed complex-valued memristive neural networks, Neural Process. Lett., 51 (2020), 193–209. https://doi.org/10.1007/s11063-019-10082-0 doi: 10.1007/s11063-019-10082-0
    [28] Z. Q. Zhang, S. H. Yu, Global asymptotic stability for a class of complex-valued Cohen-Grossberg neural networks with time delays, Neurocomputing, 171 (2016), 1158–1166. https://doi.org/10.1016/j.neucom.2015.07.051 doi: 10.1016/j.neucom.2015.07.051
    [29] Z. Q. Zhang, D. L. Hao, D. M. Zhou, Global asymptotic stability by complex-valued inequalities for complex-valued neural networks with delays on periodic time scales, Neurocomputing, 219 (2017), 494–501. https://doi.org/10.1016/j.neucom.2016.09.055 doi: 10.1016/j.neucom.2016.09.055
    [30] C. J. Xu, M. X. Liao, P. L. Li, Z. X. Liu, S. Yuan, New results on pseudo almost periodic solutions of quaternion-valued fuzzy cellular neural networks with delays, Fuzzy Set. Syst., 411 (2021), 25–47. https://doi.org/10.1016/j.fss.2020.03.016 doi: 10.1016/j.fss.2020.03.016
    [31] C. J. Xu, Z. X. Liu, M. X. Liao, P. L. Li, Q. M. Xiao, S. Yuan, Fractional-order bidirectional associate memory (BAM) neural networks with multiple delays: The case of Hopf bifurcation, Math. Comput. Simulat., 182 (2021), 471–494. https://doi.org/10.1016/j.matcom.2020.11.023 doi: 10.1016/j.matcom.2020.11.023
    [32] C. J. Xu, Z. X. Liu, L. Y. Yao, C. Aouit, Further exploration on bifurcation of fractional-order sixneuron bidirectional associative memory neural networks with multi-delays, Appl. Math. Comput., 410 (2021), 126458. https://doi.org/10.1016/j.amc.2021.126458 doi: 10.1016/j.amc.2021.126458
    [33] C. J. Xu, M. X. Liao, P. L. Li, Y. Guo, Q. M. Xiao, S. Yuan, Influence of multiple time delays on bifurcation of fractional-order neural networks, Appl. Math. Comput., 361 (2019), 565–582. https://doi.org/10.1016/j.amc.2019.05.057 doi: 10.1016/j.amc.2019.05.057
    [34] R. Zhao, B. X. Wang, J. G. Jian, Lagrange stability of BAM quaternion-valued inertial neural networks via auxiliary function-based integral inequalities, Neural Process. Lett., 2022. https://doi.org/10.1007/s11063-021-10685-6 doi: 10.1007/s11063-021-10685-6
    [35] J. Liu, J. G. Jian, B. X. Wang, Stability analysis for quaternion-valued BAM inertial neural networks with time delay via nonlinear measure approach, Math. Comput. Simulat., 174 (2020), 134–152. https://doi.org/10.1016/j.matcom.2020.03.002 doi: 10.1016/j.matcom.2020.03.002
    [36] C. J. Xu, M. X. Liao, P. L. Li, Y. Guo, Z. X. Liu, Bifurcation properties for fractional order delayed BAM neural networks, Cogn. Comput., 13 (2021), 322–356. https://doi.org/10.1007/s12559-020-09782-w doi: 10.1007/s12559-020-09782-w
    [37] C. J. Xu, W. Zhang, C. Aouit, Z. X. Liu, M. X. Liao, P. L. Li, Further investigation on bifurcation and their control of fractional-order bidirectional associative memory neural networks involving four neurons and multiple delays, Math. Method. Appl. Sci., 2021. https://doi.org/10.1002/mma.7581 doi: 10.1002/mma.7581
    [38] C. J. Xu, M. X. Liao, P. L. Li, S. Yuan, Impact of leakage delay on bifurcation in fractional-order complex-valued neural networks, Chaos Soliton. Fract., 142 (2021), 110535. https://doi.org/10.1016/j.chaos.2020.110535 doi: 10.1016/j.chaos.2020.110535
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