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Published in: Neural Processing Letters 2/2021

08-02-2021

Synchronization of Fractional Order Neutral Type Fuzzy Cellular Neural Networks with Discrete and Distributed Delays via State Feedback Control

Authors: M. Syed Ali, M. Hymavathi

Published in: Neural Processing Letters | Issue 2/2021

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Abstract

The motivation behind this paper is to explore the issue of synchronization of fractional order neutral type fuzzy cellular neural networks with state feedback control. A novel fuzzy model state feedback controller is designed. By developing Lyapunov–Krasovskii (L–K) functional, utilizing improved Jensen’s inequalities we derived sufficient conditions in terms of linear matrix inequalities (LMIs). The condition is presented in terms of LMIs, which can be easily checked by using MATLAB LMI toolbox. Finally, numerical examples are provided to show the effectiveness of the main results.

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Literature
1.
go back to reference Podlubny I (1999) Fractional differential equations. Academic Press, San DiegoMATH Podlubny I (1999) Fractional differential equations. Academic Press, San DiegoMATH
2.
go back to reference Kilbas AA, Srivastava HM, Trujillo JJ (2006) Theory and applications of fractional differential equations. Elsevier, New York, pp 1–540MATH Kilbas AA, Srivastava HM, Trujillo JJ (2006) Theory and applications of fractional differential equations. Elsevier, New York, pp 1–540MATH
3.
4.
go back to reference He JM, Chen FQ (2017) A new fractional order hyper chaotic Rabinovich system and its dynamical behaviors. Int J Non Linear Mech 95:73–81CrossRef He JM, Chen FQ (2017) A new fractional order hyper chaotic Rabinovich system and its dynamical behaviors. Int J Non Linear Mech 95:73–81CrossRef
5.
go back to reference Luo SK, He JM, Xu YL, Zhang XT (2016) Fractional generalized Hamilton method for equilibrium stability of dynamical systems. Appl Math Lett 60:14–20MathSciNetMATHCrossRef Luo SK, He JM, Xu YL, Zhang XT (2016) Fractional generalized Hamilton method for equilibrium stability of dynamical systems. Appl Math Lett 60:14–20MathSciNetMATHCrossRef
6.
go back to reference He JM, Xu YL, Luo SK (2015) Stability for manifolds of the equilibrium state of fractional Birkhoffian systems. Acta Mech 226:2135–2146MathSciNetMATHCrossRef He JM, Xu YL, Luo SK (2015) Stability for manifolds of the equilibrium state of fractional Birkhoffian systems. Acta Mech 226:2135–2146MathSciNetMATHCrossRef
7.
go back to reference Baleanu D, Inc M, Yusuf A, Aliyu AI (2017) Time fractional third-order evolution equation: symmetry analysis, explicit solutions, and conservation laws. J Comput Nonlinear Dyn 13:021011MATHCrossRef Baleanu D, Inc M, Yusuf A, Aliyu AI (2017) Time fractional third-order evolution equation: symmetry analysis, explicit solutions, and conservation laws. J Comput Nonlinear Dyn 13:021011MATHCrossRef
8.
go back to reference He J, Chen F (2018) Dynamical analysis of a new fractionalorder Rabinovich system and its fractional matrix projective synchronization. Chin J Phys 56:2627–2637CrossRef He J, Chen F (2018) Dynamical analysis of a new fractionalorder Rabinovich system and its fractional matrix projective synchronization. Chin J Phys 56:2627–2637CrossRef
9.
go back to reference He J, Chen F, Lei T (2018) Fractional matrix and inverse matrix projective synchronization methods for synchronizing the disturbed fractional-order hyper chaotic system. Math Methods Appl Sci 41:6907–6920MathSciNetMATHCrossRef He J, Chen F, Lei T (2018) Fractional matrix and inverse matrix projective synchronization methods for synchronizing the disturbed fractional-order hyper chaotic system. Math Methods Appl Sci 41:6907–6920MathSciNetMATHCrossRef
10.
go back to reference Jajarmi A, Hajipour M, Mohammadzadeh E, Baleanu D (2018) A new approach for the nonlinear fractional optimal control problems with external persistent disturbances. J Franklin Inst 355:3938–3967MathSciNetMATHCrossRef Jajarmi A, Hajipour M, Mohammadzadeh E, Baleanu D (2018) A new approach for the nonlinear fractional optimal control problems with external persistent disturbances. J Franklin Inst 355:3938–3967MathSciNetMATHCrossRef
11.
go back to reference Huang CD, Cai LM, Cao JD (2018) Linear control for synchronization of a fractional-order time-delayed chaotic financial system. Chaos Solitons Fractals 113:326–332MathSciNetMATHCrossRef Huang CD, Cai LM, Cao JD (2018) Linear control for synchronization of a fractional-order time-delayed chaotic financial system. Chaos Solitons Fractals 113:326–332MathSciNetMATHCrossRef
12.
go back to reference Yang XJ, Machado JA (2017) A new fractional operator of variable order: application in the description of anomalous diffusion. Physica A 481:276–283MathSciNetCrossRef Yang XJ, Machado JA (2017) A new fractional operator of variable order: application in the description of anomalous diffusion. Physica A 481:276–283MathSciNetCrossRef
13.
go back to reference Kiani A, Fallahi BK, Pariz N, Leung H (2009) A chaotic secure communication scheme using fractional chaotic systems based on an extended fractional Kalman filter. Commun Nonlinear Sci Numer Simul 14:863–879MathSciNetMATHCrossRef Kiani A, Fallahi BK, Pariz N, Leung H (2009) A chaotic secure communication scheme using fractional chaotic systems based on an extended fractional Kalman filter. Commun Nonlinear Sci Numer Simul 14:863–879MathSciNetMATHCrossRef
14.
go back to reference Xu X, Qiao Z, Lei Y (2018) Repetitive transient extraction for machinery fault diagnosisusing multi scale fractional order entropy infogram. Mech Syst Signal Process 103:312–326CrossRef Xu X, Qiao Z, Lei Y (2018) Repetitive transient extraction for machinery fault diagnosisusing multi scale fractional order entropy infogram. Mech Syst Signal Process 103:312–326CrossRef
16.
go back to reference Liu H, Xie G, Yu M (2019) Necessary and sufficient conditions for containment control of fractional-order multi-agent systems. Neurocomputing 323:86–95CrossRef Liu H, Xie G, Yu M (2019) Necessary and sufficient conditions for containment control of fractional-order multi-agent systems. Neurocomputing 323:86–95CrossRef
18.
go back to reference Gao Z, Liao X (2013) Robust stability criterion of fractional-order functions for interval fractional-order systems. IET Control Theory Appl 7:60–67MathSciNetCrossRef Gao Z, Liao X (2013) Robust stability criterion of fractional-order functions for interval fractional-order systems. IET Control Theory Appl 7:60–67MathSciNetCrossRef
19.
22.
go back to reference Roska T, Chua LO (1992) Cellular neural networks with nonlinear and delay-type template elements and nonuniform grids. Int J Circuit Theory Appl 20:469–481MATHCrossRef Roska T, Chua LO (1992) Cellular neural networks with nonlinear and delay-type template elements and nonuniform grids. Int J Circuit Theory Appl 20:469–481MATHCrossRef
23.
go back to reference Harrer H, Nossek JA (1992) Discrete-time cellular neural networks. Int J Circuit Theory Appl 20:453–467MATHCrossRef Harrer H, Nossek JA (1992) Discrete-time cellular neural networks. Int J Circuit Theory Appl 20:453–467MATHCrossRef
24.
go back to reference Yager RR, Zadeh LA (1992) An introduction to fuzzy logic application in intelligent systems. Springer, New York, pp 1–356 Yager RR, Zadeh LA (1992) An introduction to fuzzy logic application in intelligent systems. Springer, New York, pp 1–356
25.
go back to reference Kandel A (1982) Fuzzy techniques in pattern recognition, vol 356. Wiley, New YorkMATH Kandel A (1982) Fuzzy techniques in pattern recognition, vol 356. Wiley, New YorkMATH
26.
go back to reference Marks RJ II (1994) Fuzzy logic technology and applications. IEEE Trans Eng Manag 40:237–254MATH Marks RJ II (1994) Fuzzy logic technology and applications. IEEE Trans Eng Manag 40:237–254MATH
27.
go back to reference Zadeh LA, Fu KS, Tanaka K, Shimura M (1974) Fuzzy sets and their applications to cognitive and decision processes. IEEE Trans Circuits Syst 7:122–123 Zadeh LA, Fu KS, Tanaka K, Shimura M (1974) Fuzzy sets and their applications to cognitive and decision processes. IEEE Trans Circuits Syst 7:122–123
28.
go back to reference Ratnavelu K, Kalpana M, Balasubramaniam P, Wong K, Raveendran P (2017) Image encryption method based on chaotic fuzzy cellular neural networks. Signal Process 140:87–96CrossRef Ratnavelu K, Kalpana M, Balasubramaniam P, Wong K, Raveendran P (2017) Image encryption method based on chaotic fuzzy cellular neural networks. Signal Process 140:87–96CrossRef
29.
go back to reference Yang T, Yang LB (1997) Application of fuzzy cellular neural networks to Euclidean distance transformation. IEEE 44:242–246 Yang T, Yang LB (1997) Application of fuzzy cellular neural networks to Euclidean distance transformation. IEEE 44:242–246
30.
go back to reference Yang T, Yang LB (1996) The global stability of fuzzy cellular neural network. IEEE 43:880–883MathSciNet Yang T, Yang LB (1996) The global stability of fuzzy cellular neural network. IEEE 43:880–883MathSciNet
31.
go back to reference Ratnavelu K, Kalpana M, Balasubramaniam P (2018) Stability analysis of fuzzy genetic regulatory networks with various time delays. Bull Malays Math Sci Soc 41:491–505MathSciNetMATHCrossRef Ratnavelu K, Kalpana M, Balasubramaniam P (2018) Stability analysis of fuzzy genetic regulatory networks with various time delays. Bull Malays Math Sci Soc 41:491–505MathSciNetMATHCrossRef
32.
go back to reference Ali MS, Balasubramaniam P, Zhu Q (2017) Stability of stochastic fuzzy BAM neural networks with discrete and distributed time-varying delays. Int J Mach Learn Cybern 8:263–273CrossRef Ali MS, Balasubramaniam P, Zhu Q (2017) Stability of stochastic fuzzy BAM neural networks with discrete and distributed time-varying delays. Int J Mach Learn Cybern 8:263–273CrossRef
33.
go back to reference Ali MS, Balasubramaniam P, Rihan FA, Lakshmanan S (2016) Stability criteria for stochastic T–S fuzzy Cohen–Grossberg BAM neural networks with mixed time-varying delays. Complexity 21:143–154MathSciNetCrossRef Ali MS, Balasubramaniam P, Rihan FA, Lakshmanan S (2016) Stability criteria for stochastic T–S fuzzy Cohen–Grossberg BAM neural networks with mixed time-varying delays. Complexity 21:143–154MathSciNetCrossRef
34.
go back to reference Yang J, Luo WP, Shi KB, Zhao X (2016) Robust stability analysis of uncertain TS fuzzy systems with time-varying delay by improved delay-partitioning approach. J Nonlinear Sci Appl 9:171–185MathSciNetMATHCrossRef Yang J, Luo WP, Shi KB, Zhao X (2016) Robust stability analysis of uncertain TS fuzzy systems with time-varying delay by improved delay-partitioning approach. J Nonlinear Sci Appl 9:171–185MathSciNetMATHCrossRef
35.
go back to reference Chen H, Zhong S, Liu X, Li Y, Shi K (2017) Improved results on nonlinear perturbed T–S fuzzy system with mixed delays. J Franklin Inst 354:2032–2052MathSciNetMATHCrossRef Chen H, Zhong S, Liu X, Li Y, Shi K (2017) Improved results on nonlinear perturbed T–S fuzzy system with mixed delays. J Franklin Inst 354:2032–2052MathSciNetMATHCrossRef
36.
37.
go back to reference Balasubramaniam P, Vembarasan V (2011) Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses. Comput Math Appl 62:1838–1861MathSciNetMATHCrossRef Balasubramaniam P, Vembarasan V (2011) Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses. Comput Math Appl 62:1838–1861MathSciNetMATHCrossRef
38.
go back to reference Park MJ, Kwon OM, Park JH, Lee SM (2012) Simplified stability criteria for fuzzy Markovian jumping Hopfield neural networks of neutral type with interval time-varying delays. Expert Syst Appl 39:5625–5633CrossRef Park MJ, Kwon OM, Park JH, Lee SM (2012) Simplified stability criteria for fuzzy Markovian jumping Hopfield neural networks of neutral type with interval time-varying delays. Expert Syst Appl 39:5625–5633CrossRef
39.
go back to reference Arik S (2019) A modified Lyapunov functional with application to stability of neutral type neural networks with time delays. J Franklin Inst 356:276–291MathSciNetMATHCrossRef Arik S (2019) A modified Lyapunov functional with application to stability of neutral type neural networks with time delays. J Franklin Inst 356:276–291MathSciNetMATHCrossRef
40.
go back to reference Sathy R, Balasubramaniam P (2012) Direct delay decomposition approach to robust stability on fuzzy Markov-type BAM neural networks with time-varying delays. Springer, Berlin, pp 245–254 Sathy R, Balasubramaniam P (2012) Direct delay decomposition approach to robust stability on fuzzy Markov-type BAM neural networks with time-varying delays. Springer, Berlin, pp 245–254
41.
go back to reference Yang LX, Jiang J (2014) Adaptive synchronization of drive response fractional-order complex dynamical networks with uncertain parameters. Commun Nonlinear Sci Numer Simul 19:1496–1506MathSciNetMATHCrossRef Yang LX, Jiang J (2014) Adaptive synchronization of drive response fractional-order complex dynamical networks with uncertain parameters. Commun Nonlinear Sci Numer Simul 19:1496–1506MathSciNetMATHCrossRef
42.
go back to reference Bao H, Park JH, Cao J (2016) Synchronization of fractional order complex-valued neural networks with time delay. Neural Netw 81:16–28MATHCrossRef Bao H, Park JH, Cao J (2016) Synchronization of fractional order complex-valued neural networks with time delay. Neural Netw 81:16–28MATHCrossRef
43.
go back to reference Komanovskii VB, Nosov VR (1986) Stability of functional differential equations, vol 34. Academic Press, Cambridge, pp 682–684 Komanovskii VB, Nosov VR (1986) Stability of functional differential equations, vol 34. Academic Press, Cambridge, pp 682–684
44.
go back to reference Kuang Y (2012) Delay differential equations with applications in population dynamical system. Academic Press, Cambridge, p 412 Kuang Y (2012) Delay differential equations with applications in population dynamical system. Academic Press, Cambridge, p 412
45.
go back to reference Yao L (2017) Global exponential convergence of neutral type shunting inhibitory cellular neural networks with D operator. Neural Process Lett 45:401–409CrossRef Yao L (2017) Global exponential convergence of neutral type shunting inhibitory cellular neural networks with D operator. Neural Process Lett 45:401–409CrossRef
46.
go back to reference Yao L (2018) Global convergence of CNNs with neutral type delays and D operator. Neural Comput Appl 29:105–109CrossRef Yao L (2018) Global convergence of CNNs with neutral type delays and D operator. Neural Comput Appl 29:105–109CrossRef
47.
go back to reference Chen Z (2013) A shunting inhibitory cellular neural network with leakage delays and continuously distributed delays of neutral type. Neural Comput Appl 23:2429–2434CrossRef Chen Z (2013) A shunting inhibitory cellular neural network with leakage delays and continuously distributed delays of neutral type. Neural Comput Appl 23:2429–2434CrossRef
48.
go back to reference Xu CJ, Li PL (2018) On anti-periodic solutions for neutral shunting inhibitory cellular neural networks with time-varying delays and D operator. Neurocomputing 275:377–382CrossRef Xu CJ, Li PL (2018) On anti-periodic solutions for neutral shunting inhibitory cellular neural networks with time-varying delays and D operator. Neurocomputing 275:377–382CrossRef
49.
go back to reference Balasubramaniam P, Vembarasan V (2011) Robust stability of uncertain fuzzy BAM neural networks of neutral-type Markovian jumping parameters and impulses. Comput Math Appl 62:1838–1861MathSciNetMATHCrossRef Balasubramaniam P, Vembarasan V (2011) Robust stability of uncertain fuzzy BAM neural networks of neutral-type Markovian jumping parameters and impulses. Comput Math Appl 62:1838–1861MathSciNetMATHCrossRef
50.
go back to reference Park JH (2009) Synchronization of cellular neural networks of neutral type via dynamic feedback controller. Chaos Solitons Fractals 42:1299–1304MathSciNetMATHCrossRef Park JH (2009) Synchronization of cellular neural networks of neutral type via dynamic feedback controller. Chaos Solitons Fractals 42:1299–1304MathSciNetMATHCrossRef
51.
go back to reference Aouiti C, Dridi F, Karray F (2018) New results on neutral type fuzzy based cellular neural networks. In: IEEE international conference on fuzzy systems (FUZZ-IEEE), pp 1–8 Aouiti C, Dridi F, Karray F (2018) New results on neutral type fuzzy based cellular neural networks. In: IEEE international conference on fuzzy systems (FUZZ-IEEE), pp 1–8
52.
go back to reference Kong F, Rathinasamy S (2020) Delay-dependent criteria for general decay synchronization of discontinuous fuzzy neutral-type neural networks with time-varying delays. Int J Robust Nonlinear Control 62:1–28MathSciNet Kong F, Rathinasamy S (2020) Delay-dependent criteria for general decay synchronization of discontinuous fuzzy neutral-type neural networks with time-varying delays. Int J Robust Nonlinear Control 62:1–28MathSciNet
53.
go back to reference Long S, Jia L (2011) Stability analysis of neutral-type fuzzy neural networks with distributed delays. In: Seventh international conference on computational intelligence and security, Hainan, pp 407–411 Long S, Jia L (2011) Stability analysis of neutral-type fuzzy neural networks with distributed delays. In: Seventh international conference on computational intelligence and security, Hainan, pp 407–411
54.
55.
go back to reference Yang X, Cao J, Ho DW (2015) Exponential synchronization of discontinuous neural networks with time-varying mixed delays via state feedback and impulsive control. Cogn Neurodyn 9:113–128CrossRef Yang X, Cao J, Ho DW (2015) Exponential synchronization of discontinuous neural networks with time-varying mixed delays via state feedback and impulsive control. Cogn Neurodyn 9:113–128CrossRef
56.
go back to reference Rodrigues L, Boyd S (2005) Piecewise-affine state feedback for piecewise-affine slab systems using convex optimization. Syst Control Lett 54:835–853MathSciNetMATHCrossRef Rodrigues L, Boyd S (2005) Piecewise-affine state feedback for piecewise-affine slab systems using convex optimization. Syst Control Lett 54:835–853MathSciNetMATHCrossRef
57.
go back to reference Abdulwahhab OW, Abbas NH (2018) Design and stability analysis of a fractional order state feedback controller for trajectory tracking of a differential drive robot. Int J Control Autom Syst 16:2790–2800CrossRef Abdulwahhab OW, Abbas NH (2018) Design and stability analysis of a fractional order state feedback controller for trajectory tracking of a differential drive robot. Int J Control Autom Syst 16:2790–2800CrossRef
58.
go back to reference Jagannathan S, He P (2008) Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form. IEEE Trans Neural Netw 19:2073–2087CrossRef Jagannathan S, He P (2008) Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form. IEEE Trans Neural Netw 19:2073–2087CrossRef
59.
go back to reference Debbache G, Bennia A, Golea N (2007) Neural networks-based adaptive state feedback control of robot manipulators. Int J Comput Commun Control 2:328–339MATHCrossRef Debbache G, Bennia A, Golea N (2007) Neural networks-based adaptive state feedback control of robot manipulators. Int J Comput Commun Control 2:328–339MATHCrossRef
60.
go back to reference Huang C, Long X, Cao J (2020) Stability of antiperiodic recurrent neural networks with multiproportional delays. Math Methods Appl Sci 43:6093–6102MathSciNetMATHCrossRef Huang C, Long X, Cao J (2020) Stability of antiperiodic recurrent neural networks with multiproportional delays. Math Methods Appl Sci 43:6093–6102MathSciNetMATHCrossRef
61.
go back to reference Arik S (2002) An analysis of global asymptotic stability of delayed cellular neural networks. IEEE Trans Neural Netw 13:1239–1242CrossRef Arik S (2002) An analysis of global asymptotic stability of delayed cellular neural networks. IEEE Trans Neural Netw 13:1239–1242CrossRef
62.
go back to reference Faydasicok O (2020) New criteria for global stability of neutral-type Cohen–Grossberg neural networks with multiple delays. Neural Netw 125:330–337MATHCrossRef Faydasicok O (2020) New criteria for global stability of neutral-type Cohen–Grossberg neural networks with multiple delays. Neural Netw 125:330–337MATHCrossRef
63.
go back to reference Guo Y, Xu C (2014) Global asymptotic stability of a class of neural networks with time varying delays. In: Proceedings of 2014 IEEE Chinese guidance, navigation and control conference, pp 72–76 Guo Y, Xu C (2014) Global asymptotic stability of a class of neural networks with time varying delays. In: Proceedings of 2014 IEEE Chinese guidance, navigation and control conference, pp 72–76
64.
go back to reference Huang C, Qiao Y, Huang L, Agarwal RP (2018) Dynamical behaviors of a food-chain model with stage structure and time delays. Adv Differ Equ 2018:186MathSciNetMATHCrossRef Huang C, Qiao Y, Huang L, Agarwal RP (2018) Dynamical behaviors of a food-chain model with stage structure and time delays. Adv Differ Equ 2018:186MathSciNetMATHCrossRef
65.
go back to reference Huang C, Yang X, Cao J (2020) Stability analysis of Nicholson’s blowflies equation with two different delays. Math Comput Simul 171:201–206MathSciNetMATHCrossRef Huang C, Yang X, Cao J (2020) Stability analysis of Nicholson’s blowflies equation with two different delays. Math Comput Simul 171:201–206MathSciNetMATHCrossRef
66.
go back to reference Rajchakit G, Pratap A, Raja R, Cao J, Alzabut J, Huang C (2019) Hybrid control scheme for projective lag synchronization of Riemann–Liouville sense fractional order memristive BAM neural networks with mixed delays. Mathematics 7:759CrossRef Rajchakit G, Pratap A, Raja R, Cao J, Alzabut J, Huang C (2019) Hybrid control scheme for projective lag synchronization of Riemann–Liouville sense fractional order memristive BAM neural networks with mixed delays. Mathematics 7:759CrossRef
67.
go back to reference Zhang H, Qian C (2020) Convergence analysis on inertial proportional delayed neural networks. Adv Differ Equ 2020:277MathSciNetCrossRef Zhang H, Qian C (2020) Convergence analysis on inertial proportional delayed neural networks. Adv Differ Equ 2020:277MathSciNetCrossRef
68.
go back to reference Wang W (2018) Finite-time synchronization for a class of fuzzy cellular neural networks with time-varying coefficients and proportional delays. Fuzzy Sets Syst 338:40–49MathSciNetMATHCrossRef Wang W (2018) Finite-time synchronization for a class of fuzzy cellular neural networks with time-varying coefficients and proportional delays. Fuzzy Sets Syst 338:40–49MathSciNetMATHCrossRef
69.
go back to reference Pratap A, Raja R, Alzabut J, Cao J, Rajchakit G, Huang C (2020) Mittag–Leffler stability and adaptive impulsive synchronization of fractional order neural networks in quaternion field. Math Methods Appl Sci 43:1–31MathSciNetMATHCrossRef Pratap A, Raja R, Alzabut J, Cao J, Rajchakit G, Huang C (2020) Mittag–Leffler stability and adaptive impulsive synchronization of fractional order neural networks in quaternion field. Math Methods Appl Sci 43:1–31MathSciNetMATHCrossRef
70.
go back to reference Chen J, Zeng Z, Jiang P (2014) Global Mittag–Leffler stability and synchronization of memristor-based fractional-order neural networks. Neural Netw 51:1–8MATHCrossRef Chen J, Zeng Z, Jiang P (2014) Global Mittag–Leffler stability and synchronization of memristor-based fractional-order neural networks. Neural Netw 51:1–8MATHCrossRef
71.
go back to reference Gu K (2000) An integral inequality in the stability problem of time-delay systems, pp 2805–2810. IEEE Gu K (2000) An integral inequality in the stability problem of time-delay systems, pp 2805–2810. IEEE
72.
go back to reference Liu S, Zhou XF, Li XY, Jiang W (2016) Stability of fractional nonlinear singular systems and its applications in synchronization of complex dynamical networks. Nonlinear Dyn 84:2377–2385MathSciNetMATHCrossRef Liu S, Zhou XF, Li XY, Jiang W (2016) Stability of fractional nonlinear singular systems and its applications in synchronization of complex dynamical networks. Nonlinear Dyn 84:2377–2385MathSciNetMATHCrossRef
73.
go back to reference Boyd S, Ghaoui L, Feron E, Balakrishnan V (1994) Linear matrix inequalities in system and control theory. Society for Industrial and Applied Mathematics, PhiladelphiaMATHCrossRef Boyd S, Ghaoui L, Feron E, Balakrishnan V (1994) Linear matrix inequalities in system and control theory. Society for Industrial and Applied Mathematics, PhiladelphiaMATHCrossRef
74.
go back to reference Maboobi SH, Shahrokhi M, Pishkenari HN (2006) Observer-based control design for three well-known chaotic systems. Chaos Solitions Fractals 29:381–392MathSciNetMATHCrossRef Maboobi SH, Shahrokhi M, Pishkenari HN (2006) Observer-based control design for three well-known chaotic systems. Chaos Solitions Fractals 29:381–392MathSciNetMATHCrossRef
Metadata
Title
Synchronization of Fractional Order Neutral Type Fuzzy Cellular Neural Networks with Discrete and Distributed Delays via State Feedback Control
Authors
M. Syed Ali
M. Hymavathi
Publication date
08-02-2021
Publisher
Springer US
Published in
Neural Processing Letters / Issue 2/2021
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-020-10413-6

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