Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks

Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36...
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Gespeichert in:

Autor*in:	Zeng, Qinjun [verfasserIn] Jiang, Minghui Hu, Junhao

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Dynamically complex networks Sampled-data controlling Asymptotical synchronization Exponential synchronization

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: SN applied sciences - [Cham] : Springer International Publishing, 2019, 5(2023), 11 vom: 29. Okt.
Übergeordnetes Werk:	volume:5 ; year:2023 ; number:11 ; day:29 ; month:10

Links:	Volltext

DOI / URN:	10.1007/s42452-023-05515-4

Katalog-ID:	SPR053570278

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520			\|a Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results.
520			\|a Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval.
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allfields	10.1007/s42452-023-05515-4 doi (DE-627)SPR053570278 (SPR)s42452-023-05515-4-e DE-627 ger DE-627 rakwb eng Zeng, Qinjun verfasserin aut Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213 Jiang, Minghui aut Hu, Junhao aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 5(2023), 11 vom: 29. Okt. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:5 year:2023 number:11 day:29 month:10 https://dx.doi.org/10.1007/s42452-023-05515-4 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2023 11 29 10
spelling	10.1007/s42452-023-05515-4 doi (DE-627)SPR053570278 (SPR)s42452-023-05515-4-e DE-627 ger DE-627 rakwb eng Zeng, Qinjun verfasserin aut Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213 Jiang, Minghui aut Hu, Junhao aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 5(2023), 11 vom: 29. Okt. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:5 year:2023 number:11 day:29 month:10 https://dx.doi.org/10.1007/s42452-023-05515-4 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2023 11 29 10
allfields_unstemmed	10.1007/s42452-023-05515-4 doi (DE-627)SPR053570278 (SPR)s42452-023-05515-4-e DE-627 ger DE-627 rakwb eng Zeng, Qinjun verfasserin aut Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213 Jiang, Minghui aut Hu, Junhao aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 5(2023), 11 vom: 29. Okt. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:5 year:2023 number:11 day:29 month:10 https://dx.doi.org/10.1007/s42452-023-05515-4 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2023 11 29 10
allfieldsGer	10.1007/s42452-023-05515-4 doi (DE-627)SPR053570278 (SPR)s42452-023-05515-4-e DE-627 ger DE-627 rakwb eng Zeng, Qinjun verfasserin aut Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213 Jiang, Minghui aut Hu, Junhao aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 5(2023), 11 vom: 29. Okt. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:5 year:2023 number:11 day:29 month:10 https://dx.doi.org/10.1007/s42452-023-05515-4 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2023 11 29 10
allfieldsSound	10.1007/s42452-023-05515-4 doi (DE-627)SPR053570278 (SPR)s42452-023-05515-4-e DE-627 ger DE-627 rakwb eng Zeng, Qinjun verfasserin aut Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213 Jiang, Minghui aut Hu, Junhao aut Enthalten in SN applied sciences [Cham] : Springer International Publishing, 2019 5(2023), 11 vom: 29. Okt. (DE-627)103761139X (DE-600)2947292-1 2523-3971 nnns volume:5 year:2023 number:11 day:29 month:10 https://dx.doi.org/10.1007/s42452-023-05515-4 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2023 11 29 10
language	English
source	Enthalten in SN applied sciences 5(2023), 11 vom: 29. Okt. volume:5 year:2023 number:11 day:29 month:10
sourceStr	Enthalten in SN applied sciences 5(2023), 11 vom: 29. Okt. volume:5 year:2023 number:11 day:29 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Dynamically complex networks Sampled-data controlling Asymptotical synchronization Exponential synchronization
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container_title	SN applied sciences
authorswithroles_txt_mv	Zeng, Qinjun @@aut@@ Jiang, Minghui @@aut@@ Hu, Junhao @@aut@@
publishDateDaySort_date	2023-10-29T00:00:00Z
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First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. 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author	Zeng, Qinjun
spellingShingle	Zeng, Qinjun misc Dynamically complex networks misc Sampled-data controlling misc Asymptotical synchronization misc Exponential synchronization Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
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topic_title	Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks Dynamically complex networks (dpeaa)DE-He213 Sampled-data controlling (dpeaa)DE-He213 Asymptotical synchronization (dpeaa)DE-He213 Exponential synchronization (dpeaa)DE-He213
topic	misc Dynamically complex networks misc Sampled-data controlling misc Asymptotical synchronization misc Exponential synchronization
topic_unstemmed	misc Dynamically complex networks misc Sampled-data controlling misc Asymptotical synchronization misc Exponential synchronization
topic_browse	misc Dynamically complex networks misc Sampled-data controlling misc Asymptotical synchronization misc Exponential synchronization
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title	Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
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title_full	Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
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author_browse	Zeng, Qinjun Jiang, Minghui Hu, Junhao
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doi_str_mv	10.1007/s42452-023-05515-4
title_sort	free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
title_auth	Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
abstract	Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. © The Author(s) 2023
abstractGer	Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. © The Author(s) 2023
abstract_unstemmed	Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results. Article highlights Time-dependent continuous Lyapunov functions are created with sufficient reliable data about the current sampling sequence to lower the restrictiveness of the suggested conclusions.Modified free-matrix-based integral inequalities (MFMBIIs) are proposed.Numerical examples demonstrate how our findings can be used to get a larger upper constraint on the sampling interval. © The Author(s) 2023
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title_short	Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks
url	https://dx.doi.org/10.1007/s42452-023-05515-4
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author2	Jiang, Minghui Hu, Junhao
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Free-matrix-based integral inequalities for sampled-data synchronization control of delayed complex networks

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