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PureMathematicsnØêÆ,2021,11(7),1369-1378
PublishedOnlineJuly2021inHans.http://www.hanspub.org/journal/pm
https://doi.org/10.12677/pm.2021.117154
äžCXêÚž¢[œ ²ä
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444§§§ÜÜÜttt‚‚‚§§§¶¶¶UUU
∗
þ°“‰ŒÆ§ênÆ§þ°
Email:
∗
dingwei@shnu.edu.cn
ÂvFϵ2021c611F¶¹^Fϵ2021c713F¶uÙFϵ2021c721F
Á‡
©ïÄ´äkžCXêÚžCž¢[œ ²ä(FCNNs)½žmÓÚ¯K§8
´ÏLEÜ·››ì§¦ü‡äkžCXêÚžCž¢FCNNs3k•žmSÓÚ§¿…
Œ±ÏLUC››ìëê5ýk½XÚÓÚ¤I‡žm"̇•{´EÜ·››ì±
9Lyapunov¼ê§|^½žm-½5nØ9˜ØªE|§äkžCXêÚžCž¢
FCNNs½žmÓÚ˜#¿©^‡"•„‰˜‡êŠ[~fy²©Ì‡(J
k5"
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[œ ²ä§½žmÓÚ§žCXê§žCž¢
Fixed-TimeSynchronizationforFuzzy
CellularNeuralNetworkswith
Time-VaryingCoefficientsandDelays
YangLiu,SonghuanZhang,WeiDing
∗
∗ÏÕŠö"
©ÙÚ^:4,Üt‚,¶U.äžCXêÚž¢[œ ²ä½žmÓÚ[J].nØêÆ,2021,11(7):
1369-1378.
DOI:10.12677/pm.2021.117154
4
DepartmentofMathematics,ShanghaiNormalUniversity,Shanghai
Email:
∗
dingwei@shnu.edu.cn
Received:Jun.11
th
,2021;accepted:Jul.13
th
,2021;published:Jul.21
st
,2021
Abstract
This paper studiesthe fixed-timesynchronization problem offuzzycellularneural net-
works(FCNNs)withtime-varyingcoefficientsandtime-varyingdelays.Thepurpose
istobeabletomaketwoFCNNswithtime-varyingcoefficientsandtime-varyingde-
lays canbesynchronized in afinitetimeby constructing asuitablecontroller, andthe
time required forsystem synchronization can be presetby changingthe parametersof
thecontroller.ThemainmethodistoconstructasuitablecontrollerandLyapunov
function,andusethefixed-timestabilitytheoryandsomeinequalitytechniquesto
obtainsomenewsufficientconditionsforfixed-timesynchronizationofFCNNswith
time-varyingcoefficientsandtime-varyingdelays.Finally, anexampleisgiventoprove
thevalidityofthemainresultsofthispaper.
Keywords
FuzzyCellularNeuralNetwork,Fixed-TimeSynchronization,Time-Varying
Coefficient,Time-VaryingDelay
Copyright
c
2021byauthor(s)andHansPublishersInc.
This work is licensed undertheCreative Commons Attribution International License (CCBY 4.0).
http://creativecommons.org/licenses/by/4.0/
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DOI:10.12677/pm.2021.1171541370nØêÆ
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DOI:10.12677/pm.2021.1171541371nØêÆ
4
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DOI:10.12677/pm.2021.1171541372nØêÆ
4
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DOI:10.12677/pm.2021.1171541373nØêÆ
4
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i=1
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i
|e
i
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−
n
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+
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i
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i
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i
(t))|
−
n
X
i=1
ρ
i
|e
i
(t)|
λ
−
n
X
i=1
l
i
|e
i
(t)|
µ
.
DOI:10.12677/pm.2021.1171541374nØêÆ
4
d^‡(3.2)9Ún2.2 OŽ
˙
V(e(t)) ≤−
n
X
i=1
ρ
i
|e
i
(t)|
λ
−
n
X
i=1
l
i
|e
i
(t)|
µ
≤−ρ
n
X
i=1
|e
i
(t)|
λ
−l
n
X
i=1
|e
i
(t)|
µ
≤−ρn
1−λ
(
n
X
i=1
|e
i
(t)|)
λ
−l(
n
X
i=1
|e
i
(t)|)
µ
= −ρn
1−λ
V
λ
(e(t))−lV
µ
(e(t)),
Ù¥ρ=min
1≤i≤n
{ρ
i
}>0,l=min
1≤i≤n
{l
i
}>0.
ÏLÚn2.3,·‚UXÚ(2.1) Ú(2.2) Œ±3-½žmT
0
¢y½žmÓÚ,¿…
T
0
≤T
max
=
1
ρn
1−λ
(λ−1)
+
1
l(1−µ)
.y..
íØ3.1.eXÚ(2.1)Ú(2.2) ¥¤kžCXêÑòz•~ê,@o½n3.1 (ØE,¤á.
íØ3.2.eXÚ(2.1), (2.2) 9››ì(3.1) ¥¤kžCž¢t−τ
j
(t) ÑO†•'~ž¢q
ij
t,Ù
¥q
ij
∈(0,1],K½n3.1 (ØE,¤á.
53.1.©z[1]9©z[2]®²©OïÄäk~XêÚžCž¢FCNNs 9äkžCXêÚ'
~ ž¢FCNNs ,¿…Ñ´ïÄk•žmÓÚ¯K,¤O-½žmÑÚXÚЩ^‡´
ƒ'.´3˜„œ¹e,Щ^‡ØN´¼,íØ3.1 ÚíØ3.2 -½žmÑÚÐ
©^‡vk'X,íØ3.1ÚíØ3.2(J'©z[1]Ú[2]‡•\¢^.
53.2.Ï•sign ¼ê´ØëY,§ŒU¬—ËÄ,Šâ©z[1]Ž{,·‚^ëY…Š••
(−1,1) tanh ¼ê5O†.@o››ì(3.1) ÒC¤
u
i
(t) = −k
i
e
i
(t)−η
i
tanh(ξ
i
e
i
(t))|e
i
(t−τ
i
(t))|−ρ
i
tanh(%
i
e
i
(t))|e
i
(t)|
λ
−l
i
tanh(p
i
e
i
(t))|e
i
(t)|
µ
,
(3.5)
Ù¥k
i
≥0,η
i
≥0,ξ
i
>0,ρ
i
>0,%
i
>0,l
i
>0,p
i
>0,0 <µ<1 <λ,i∈J.
4.êŠ[
3ù˜!¥·‚‰˜‡‘(=n= 2)~fy©¤(Jk5.
~4.1.éuXÚ(2.1),(2.2)9››ì(3.5) kXeŠ:
α
i1
(t)=β
i1
(t)=
1+sinit
3
,α
i2
(t)=β
i2
(t)=
1+cosit
3
,c
1
(t)=
2+3sint
2
,c
2
(t)=
2+3cost
2
,a
i1
(t)=
b
i1
(t)=
1+sinit
2
,a
i2
(t)=b
i2
(t)=
1+cosit
2
,τ
j
(t)=
exp(t)
1+exp(t)
,f
j
(x)=0.5(|x+ 1|−|x−1|),I
i
(t)=
−4,T
ij
(t) = v
j
(t) = S
ij
(t) = d
ij
(t) = 1,i,j= 1,2.
Щ^‡•φ(s)=(0.2,−0.4)
T
,ϕ(s)=(−0.2,0.4)
T
.››ì(3.5) ¥kk
i
=3,η
i
=5,ρ
i
=
DOI:10.12677/pm.2021.1171541375nØêÆ
4
1,l
i
= 3,λ= 1.5,µ= 0.9,ξ
i
= %
i
= p
i
= 2.
ω
i
= 1, K²OŽŒ(A
1
), (A
2
)9^‡(3.2)Ñ÷v.¿d(3.3)Œ-½žmT
0
≤T
max
≈
6.161.Ïd,Šâ½n3.1Œ•,3››ì(3.5)e,XÚ(2.1) ÚXÚ(2.2)3T
0
žŒ¢y½žm
ÓÚ.
dMatlab ^‡ ŒXen‡ã”:ã1L²eÛ›ì(3.5) ,ØXÚ(2.3) Ø-½,KXÚ
(2.1)ÚXÚ(2.2) ØU¢yÓÚ(„ã1).ã2KL²3››ì(3.5)e,ØXÚ(2.3) 3½žm
T
0
ž-½,@oXÚ(2.1)ÚXÚ(2.2)3T
0
≤T
max
≈6.161 žU½žmÓÚ(„ã2).
Figure1.Timeevolutionofe
1
(t)ande
2
(t)withoutthe
controller(3.5)
ã1.Û›ì(3.5)že
1
(t)Úe
2
(t);,
Figure2.Timeevolutionofe
1
(t)ande
2
(t)withthe
controller(3.5)
ã2.k››ì(3.5)že
1
(t)Úe
2
(t);,
DOI:10.12677/pm.2021.1171541376nØêÆ
4
54.1.k
i
= 1,η
i
= 1,i=1,2.K^‡(3.2) Ø÷v.lã3ŒwÑe^‡(3.2) Ø÷v,=¦3
››ì(3.5)e,XÚ(2.1)ÚXÚ(2.2) •ØU¢y½žmÓÚ§„ã3.
Figure3.Theevolutionofsynchronizationerrore
1
(t)
ande
2
(t)thatdon’tsatisfy(3.2)
ã3.Ø÷v^‡(3.2)že
1
(t)Úe
2
(t);,
Ä7‘8
©óŠdI[g,‰ÆÄ7(No.12071302)|±"
ë•©z
[1]Abdurahman,A.,Jiang,H.J.andTeng,Z.D.(2016)Finite-TimeSynchronizationforFuzzy
CellularNeuralNetworkswithTime-VaryingDelays.FuzzySetsandSystems,297,96-111.
https://doi.org/10.1016/j.fss.2015.07.009
[2]Wang, W.T.(2018) Finite-TimeSynchronization foraClass ofFuzzyCellularNeural Networks
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https://doi.org/10.1016/j.fss.2017.04.005
[3]Zheng,M.W.,Li,L.X.,Peng,H.P.,Xiao,J.H.,Yang,Y.X.,Zhang,Y.P.andZhao,H.(2018)
Fixed-TimeSynchronizationofMemristor-BasedFuzzyCellularNeuralNetworkwithTime-
VaryingDelay.JournaloftheFranklinInstitute,355,6780-6809.
https://doi.org/10.1016/j.jfranklin.2018.06.041
DOI:10.12677/pm.2021.1171541377nØêÆ
4
[4]Ding,W.andHan,M.A.(2008)SynchronizationofDelayedFuzzyCellularNeuralNetworks
BasedonAdaptiveControl.PhysicsLettersA,372,4674-4681.
https://doi.org/10.1016/j.physleta.2008.04.053
[5]Chen, C., Li, L., Peng,H., Yang, Y.andZhao,H.(2020) ANewFixed-TimeStabilityTheorem
andItsApplicationtothe Fixed-TimeSynchronization ofNeuralNetworks.NeuralNetworks,
123,412-419.https://doi.org/10.1016/j.neunet.2019.12.028
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DOI:10.12677/pm.2021.1171541378nØêÆ

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