{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T07:03:39Z","timestamp":1768979019975,"version":"3.49.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T00:00:00Z","timestamp":1736726400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T00:00:00Z","timestamp":1736726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Max Planck Institute for Dynamics of Complex Technical Systems (MPI Magdeburg)"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>We investigate the exponential synchronization of bi-directional associative memory neural networks with delays on a family of different time domains. By utilizing the theory of time scales, we provide stabilization results that are applicable to continuous-time, discrete-time, and general nonuniform hybrid time domains. Our approach employs a unified matrix-measure theory, a recent alternative to traditional Lyapunov functions, to establish exponential synchronization and design effective feedback laws. Notably, our methodology does not require symmetry or diagonality in the control gain matrix, distinguishing it from prior works. Furthermore, we explore various special cases of the considered systems and provide a detailed discussion highlighting the advantages of our findings over existing results. The effectiveness of our proposed criteria is demonstrated through small-scale and medium-scale simulated numerical examples across different time domains. Additionally, we apply our results to an example from the literature, showcasing the broad applicability and improved performance of our method in comparison to previous approaches.<\/jats:p>","DOI":"10.1007\/s00521-024-10820-z","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T22:57:17Z","timestamp":1736809037000},"page":"6383-6400","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Exponential synchronization of bi-directional associative memory neural networks with delay on arbitrary time domains"],"prefix":"10.1007","volume":"37","author":[{"given":"Vipin","family":"Kumar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7068-5426","authenticated-orcid":false,"given":"Jan","family":"Heiland","sequence":"additional","affiliation":[]},{"given":"Peter","family":"Benner","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,13]]},"reference":[{"issue":"1","key":"10820_CR1","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1109\/21.87054","volume":"18","author":"B Kosko","year":"1988","unstructured":"Kosko B (1988) Bi-directional associative memories. IEEE Trans Syst Man Cybern 18(1):49\u201360. https:\/\/doi.org\/10.1109\/21.87054","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"23","key":"10820_CR2","doi-asserted-by":"publisher","first-page":"4947","DOI":"10.1364\/ao.26.004947","volume":"26","author":"B Kosko","year":"1987","unstructured":"Kosko B (1987) Adaptive bi-directional associative memories. Appl Opt 26(23):4947. https:\/\/doi.org\/10.1364\/ao.26.004947","journal-title":"Appl Opt"},{"issue":"10","key":"10820_CR3","doi-asserted-by":"publisher","first-page":"3088","DOI":"10.1073\/pnas.81.10.3088","volume":"81","author":"JJ Hopfield","year":"1984","unstructured":"Hopfield JJ (1984) Neurons with graded response have collective computational properties like those of two-state neurons. Proc Natl Acad Sci 81(10):3088\u20133092. https:\/\/doi.org\/10.1073\/pnas.81.10.3088","journal-title":"Proc Natl Acad Sci"},{"issue":"3","key":"10820_CR4","doi-asserted-by":"publisher","first-page":"119","DOI":"10.4103\/0971-6203.42763","volume":"33","author":"N Sharma","year":"2008","unstructured":"Sharma N, Ray A, Sharma S, Shukla K, Pradhan S, Aggarwal L (2008) Segmentation and classification of medical images using texture-primitive features: application of BAM-type artificial neural network. J Med Phys 33(3):119. https:\/\/doi.org\/10.4103\/0971-6203.42763","journal-title":"J Med Phys"},{"issue":"3","key":"10820_CR5","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1117\/1.602416","volume":"39","author":"CY Chang","year":"2000","unstructured":"Chang CY (2000) Two-layer competitive based Hopfield neural network for medical image edge detection. Opt Eng 39(3):695. https:\/\/doi.org\/10.1117\/1.602416","journal-title":"Opt Eng"},{"issue":"4","key":"10820_CR6","first-page":"382","volume":"5","author":"YP Singh","year":"2009","unstructured":"Singh YP, Yadav SV, Gupta A, Khare A (2009) Bi-Directional associative memory neural network method in the character recognition. J Theor Appl Inf Technol 5(4):382\u2013386","journal-title":"J Theor Appl Inf Technol"},{"issue":"1","key":"10820_CR7","doi-asserted-by":"publisher","first-page":"174","DOI":"10.25130\/tjps.v29i1.1454","volume":"29","author":"RH Hasan","year":"2024","unstructured":"Hasan RH, Aboud IS, Hassoon RM (2024) Optical mark recognition using modify bi-directional associative memory. Tikrit J Pure Sci 29(1):174\u2013184. https:\/\/doi.org\/10.25130\/tjps.v29i1.1454","journal-title":"Tikrit J Pure Sci"},{"issue":"2","key":"10820_CR8","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1007\/s12555-018-0676-7","volume":"18","author":"Y Guo","year":"2020","unstructured":"Guo Y, Luo Y, Wang W, Luo X, Ge C, Kurths J, Yuan M, Gao Y (2020) Fixed-time synchronization of complex-valued memristive BAM neural network and applications in image encryption and decryption. Int J Control Autom Syst 18(2):462\u201376. https:\/\/doi.org\/10.1007\/s12555-018-0676-7","journal-title":"Int J Control Autom Syst"},{"key":"10820_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2024.129512","volume":"637","author":"MS Centonze","year":"2024","unstructured":"Centonze MS, Kanter I, Barra A (2024) Statistical mechanics of learning via reverberation in bidirectional associative memories. Phys A: Stat Mech Appl 637:129512. https:\/\/doi.org\/10.1016\/j.physa.2024.129512","journal-title":"Phys A: Stat Mech Appl"},{"key":"10820_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.mejo.2020.104725","volume":"98","author":"MM Majdabadi","year":"2020","unstructured":"Majdabadi MM, Shokouhi SB, Ko SB (2020) Efficient hybrid CMOS\/memristor implementation of bidirectional associative memory using passive weight array. Microelectron J 98:104725. https:\/\/doi.org\/10.1016\/j.mejo.2020.104725","journal-title":"Microelectron J"},{"key":"10820_CR11","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1016\/j.neucom.2018.11.050","volume":"330","author":"B Li","year":"2019","unstructured":"Li B, Zhao Y, Shi G (2019) A novel design of memristor-based bidirectional associative memory circuits using Verilog-AMS. Neurocomputing 330:437\u201348. https:\/\/doi.org\/10.1016\/j.neucom.2018.11.050","journal-title":"Neurocomputing"},{"key":"10820_CR12","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.sysarc.2019.02.005","volume":"94","author":"S Basu","year":"2019","unstructured":"Basu S, Karuppiah M, Nasipuri M, Halder AK, Radhakrishnan N (2019) Bio-inspired cryptosystem with DNA cryptography and neural networks. J Syst Archit 94:24\u201331. https:\/\/doi.org\/10.1016\/j.sysarc.2019.02.005","journal-title":"J Syst Archit"},{"issue":"6","key":"10820_CR13","doi-asserted-by":"publisher","first-page":"4501","DOI":"10.1007\/s00521-021-06605-3","volume":"34","author":"X Li","year":"2022","unstructured":"Li X, Liu X, Zhang S (2022) New criteria on the finite-time stability of fractional-order BAM neural networks with time delay. Neural Comput Appl 34(6):4501\u20134517. https:\/\/doi.org\/10.1007\/s00521-021-06605-3","journal-title":"Neural Comput Appl"},{"issue":"1","key":"10820_CR14","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.nonrwa.2012.07.016","volume":"14","author":"B Liu","year":"2013","unstructured":"Liu B (2013) Global exponential stability for BAM neural networks with time-varying delays in the leakage terms. Nonlinear Anal Real World Appl 14(1):559\u2013566. https:\/\/doi.org\/10.1016\/j.nonrwa.2012.07.016","journal-title":"Nonlinear Anal Real World Appl"},{"issue":"2","key":"10820_CR15","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1007\/s00521-015-1865-4","volume":"27","author":"L Li","year":"2015","unstructured":"Li L, Yang Y, Lin G (2015) The stabilization of BAM neural networks with time-varying delays in the leakage terms via sampled-data control. Neural Comput Appl 27(2):447\u2013457. https:\/\/doi.org\/10.1007\/s00521-015-1865-4","journal-title":"Neural Comput Appl"},{"issue":"2","key":"10820_CR16","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1109\/tnn.2006.886358","volume":"18","author":"J Cao","year":"2007","unstructured":"Cao J, Xiao M (2007) Stability and Hopf Bifurcation in a simplified BAM neural network with two time delays. IEEE Trans Neural Netw 18(2):416\u2013430. https:\/\/doi.org\/10.1109\/tnn.2006.886358","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"10820_CR17","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1007\/s00521-022-07791-4","volume":"35","author":"J Yang","year":"2023","unstructured":"Yang J, Li HL, Zhang L, Hu C, Jiang H (2023) Synchronization analysis and parameters identification of uncertain delayed fractional-order BAM neural networks. Neural Comput Appl 35(1):1041\u20131052. https:\/\/doi.org\/10.1007\/s00521-022-07791-4","journal-title":"Neural Comput Appl"},{"issue":"8","key":"10820_CR18","doi-asserted-by":"publisher","first-page":"3815","DOI":"10.1109\/tnnls.2017.2741349","volume":"29","author":"D Wang","year":"2018","unstructured":"Wang D, Huang L, Tang L (2018) Dissipativity and synchronization of generalized BAM neural networks with multivariate discontinuous activations. IEEE Trans Neural Netw Learn Syst 29(8):3815\u20133827. https:\/\/doi.org\/10.1109\/tnnls.2017.2741349","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10820_CR19","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.amc.2018.05.046","volume":"337","author":"M Sader","year":"2018","unstructured":"Sader M, Abdurahman A, Jiang H (2018) General decay synchronization of delayed BAM neural networks via nonlinear feedback control. Appl Math Comput 337:302\u2013314. https:\/\/doi.org\/10.1016\/j.amc.2018.05.046","journal-title":"Appl Math Comput"},{"issue":"2\u20133","key":"10820_CR20","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.physleta.2004.12.026","volume":"335","author":"J Liang","year":"2005","unstructured":"Liang J, Cao J, Ho DWC (2005) Discrete-time bi-directional associative memory neural networks with variable delays. Phys Lett A 335(2\u20133):226\u2013234. https:\/\/doi.org\/10.1016\/j.physleta.2004.12.026","journal-title":"Phys Lett A"},{"key":"10820_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-024-09462-y","author":"Z Yang","year":"2024","unstructured":"Yang Z, Zhang Z, Liao H (2024) Quasi-projective synchronization of discrete-time BAM neural networks by discrete inequality techniques. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-024-09462-y","journal-title":"Neural Comput Appl"},{"issue":"2","key":"10820_CR22","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1016\/j.cnsns.2010.04.022","volume":"16","author":"R Raja","year":"2011","unstructured":"Raja R, Marshal Anthoni S (2011) Global exponential stability of BAM neural networks with time-varying delays: the discrete-time case. Commun Nonlinear Sci 16(2):613\u2013622. https:\/\/doi.org\/10.1016\/j.cnsns.2010.04.022","journal-title":"Commun Nonlinear Sci"},{"issue":"11","key":"10820_CR23","doi-asserted-by":"publisher","first-page":"4014","DOI":"10.1002\/mma.4281","volume":"40","author":"Y Shu","year":"2017","unstructured":"Shu Y, Liu X, Wang F, Qiu S (2017) Further results on exponential stability of discrete-time BAM neural networks with time-varying delays. Math Meth Appl Sci 40(11):4014\u20134027. https:\/\/doi.org\/10.1002\/mma.4281","journal-title":"Math Meth Appl Sci"},{"key":"10820_CR24","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.neucom.2019.10.089","volume":"379","author":"EY Cong","year":"2020","unstructured":"Cong EY, Han X, Zhang X (2020) Global exponential stability analysis of discrete-time BAM neural networks with delays: a mathematical induction approach. Neurocomputing 379:227\u2013235. https:\/\/doi.org\/10.1016\/j.neucom.2019.10.089","journal-title":"Neurocomputing"},{"issue":"8","key":"10820_CR25","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1103\/physrevlett.64.821","volume":"64","author":"LM Pecora","year":"1990","unstructured":"Pecora LM, Carroll TL (1990) Synchronization in chaotic systems. Phys Rev Lett 64(8):821\u2013824. https:\/\/doi.org\/10.1103\/physrevlett.64.821","journal-title":"Phys Rev Lett"},{"issue":"4","key":"10820_CR26","doi-asserted-by":"publisher","first-page":"1877","DOI":"10.1007\/s12555-015-0462-8","volume":"15","author":"M Zarefard","year":"2017","unstructured":"Zarefard M, Effati S (2017) Adaptive synchronization between two non-identical BAM neural networks with unknown parameters and time-varying delays. Int J Control Autom Syst 15(4):1877\u20131887. https:\/\/doi.org\/10.1007\/s12555-015-0462-8","journal-title":"Int J Control Autom Syst"},{"issue":"2","key":"10820_CR27","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1007\/s11424-019-8121-4","volume":"33","author":"F Lin","year":"2019","unstructured":"Lin F, Zhang Z (2019) Global asymptotic synchronization of a class of BAM neural networks with time delays via integrating inequality techniques. J Syst Sci Complex 33(2):366\u2013382. https:\/\/doi.org\/10.1007\/s11424-019-8121-4","journal-title":"J Syst Sci Complex"},{"issue":"1","key":"10820_CR28","doi-asserted-by":"publisher","first-page":"41","DOI":"10.15388\/namc.2021.26.21204","volume":"26","author":"M Sader","year":"2021","unstructured":"Sader M, Wang F, Liu Z, Chen Z (2021) Projective synchronization analysis for BAM neural networks with time-varying delay via novel control. Nonlinear Anal Model Control 26(1):41\u201356. https:\/\/doi.org\/10.15388\/namc.2021.26.21204","journal-title":"Nonlinear Anal Model Control"},{"issue":"5","key":"10820_CR29","doi-asserted-by":"publisher","first-page":"1354","DOI":"10.4304\/jnw.9.5.1354-1360","volume":"9","author":"M Wang","year":"2014","unstructured":"Wang M, Teng J, Liu E (2014) Global exponential synchronization of delayed BAM neural networks. J Netw 9(5):1354\u20131360. https:\/\/doi.org\/10.4304\/jnw.9.5.1354-1360","journal-title":"J Netw"},{"key":"10820_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2022.112655","volume":"164","author":"D Chen","year":"2022","unstructured":"Chen D, Zhang Z (2022) Finite-time synchronization for delayed BAM neural networks by the approach of the same structural functions. Chaos Soliton Fract 164:112655. https:\/\/doi.org\/10.1016\/j.chaos.2022.112655","journal-title":"Chaos Soliton Fract"},{"issue":"1","key":"10820_CR31","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/s11063-018-9805-9","volume":"49","author":"D Xie","year":"2018","unstructured":"Xie D, Jiang Y, Han M (2018) Global exponential synchronization of complex-valued neural networks with time delays via matrix measure Method. Neural Process Lett 49(1):187\u2013201. https:\/\/doi.org\/10.1007\/s11063-018-9805-9","journal-title":"Neural Process Lett"},{"key":"10820_CR32","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.amc.2015.08.064","volume":"270","author":"H Bao","year":"2015","unstructured":"Bao H, Park JH, Cao J (2015) Matrix measure strategies for exponential synchronization and anti-synchronization of memristor-based neural networks with time-varying delays. Appl Math Comput 270:543\u2013556. https:\/\/doi.org\/10.1016\/j.amc.2015.08.064","journal-title":"Appl Math Comput"},{"issue":"1\u20132","key":"10820_CR33","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/s11071-008-9344-4","volume":"55","author":"W He","year":"2008","unstructured":"He W, Cao J (2008) Exponential synchronization of chaotic neural networks: a matrix measure approach. Nonlinear Dyn 55(1\u20132):55\u201365. https:\/\/doi.org\/10.1007\/s11071-008-9344-4","journal-title":"Nonlinear Dyn"},{"issue":"3","key":"10820_CR34","doi-asserted-by":"publisher","first-page":"1759","DOI":"10.1007\/s11071-016-2603-x","volume":"84","author":"Y Li","year":"2016","unstructured":"Li Y, Li C (2016) Matrix measure strategies for stabilization and synchronization of delayed BAM neural networks. Nonlinear Dyn 84(3):1759\u20131770. https:\/\/doi.org\/10.1007\/s11071-016-2603-x","journal-title":"Nonlinear Dyn"},{"key":"10820_CR35","unstructured":"Hilger S (1988) Ein Ma\u00dfkettenkalk\u00fcl mit Anwendung auf Zentrumsmannigfaltigkeiten. Univ, W\u00fcrzburg"},{"key":"10820_CR36","doi-asserted-by":"crossref","unstructured":"Bohner M, Peterson A (2001) Dynamic equations on time scales. Birkh\u00e4user, Boston","DOI":"10.1007\/978-1-4612-0201-1"},{"key":"10820_CR37","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.amc.2018.01.029","volume":"328","author":"L Wang","year":"2018","unstructured":"Wang L, Huang T, Xiao Q (2018) Global exponential synchronization of nonautonomous recurrent neural networks with time delays on time scales. Appl Math Comput 328:263\u2013275. https:\/\/doi.org\/10.1016\/j.amc.2018.01.029","journal-title":"Appl Math Comput"},{"issue":"8","key":"10820_CR38","doi-asserted-by":"publisher","first-page":"3567","DOI":"10.1007\/s00521-020-05183-0","volume":"33","author":"A Arbi","year":"2021","unstructured":"Arbi A, Guo Y, Cao J (2021) Convergence analysis on time scales for HOBAM neural networks in the Stepanov-like weighted pseudo almost automorphic space. Neural Comput Appl 33(8):3567\u20133581. https:\/\/doi.org\/10.1007\/s00521-020-05183-0","journal-title":"Neural Comput Appl"},{"issue":"16\u201318","key":"10820_CR39","doi-asserted-by":"publisher","first-page":"3582","DOI":"10.1016\/j.neucom.2008.06.004","volume":"71","author":"A Chen","year":"2008","unstructured":"Chen A, Du D (2008) Global exponential stability of delayed BAM network on time scale. Neurocomputing 71(16\u201318):3582\u20133588. https:\/\/doi.org\/10.1016\/j.neucom.2008.06.004","journal-title":"Neurocomputing"},{"issue":"1","key":"10820_CR40","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/s11063-009-9127-z","volume":"31","author":"Y Li","year":"2010","unstructured":"Li Y, Gao S (2010) Global exponential stability for impulsive BAM neural networks with distributed delays on time scales. Neural Process Lett 31(1):65\u201391. https:\/\/doi.org\/10.1007\/s11063-009-9127-z","journal-title":"Neural Process Lett"},{"key":"10820_CR41","doi-asserted-by":"publisher","DOI":"10.1109\/jas.2016.7510043","author":"Y Tan","year":"2017","unstructured":"Tan Y, Huang Z (2017) Synchronization of drive-response networks with delays on time scales. IEEE\/CAA J Autom Sin. https:\/\/doi.org\/10.1109\/jas.2016.7510043","journal-title":"IEEE\/CAA J Autom Sin"},{"issue":"6","key":"10820_CR42","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.1109\/tnnls.2018.2874982","volume":"30","author":"Q Xiao","year":"2019","unstructured":"Xiao Q, Huang T, Zeng Z (2019) Global exponential stability and synchronization for discrete-time inertial neural networks with time delays: a timescale approach. IEEE Trans Neural Netw Learn Syst 30(6):1854\u20131866. https:\/\/doi.org\/10.1109\/tnnls.2018.2874982","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"2","key":"10820_CR43","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1007\/s11063-018-9821-9","volume":"49","author":"M Syed Ali","year":"2018","unstructured":"Syed Ali M, Yogambigai J (2018) Synchronization criterion of complex dynamical networks with both leakage delay and coupling delay on time scales. Neural Process Lett 49(2):453\u2013466. https:\/\/doi.org\/10.1007\/s11063-018-9821-9","journal-title":"Neural Process Lett"},{"key":"10820_CR44","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.neucom.2016.07.031","volume":"216","author":"X Lu","year":"2016","unstructured":"Lu X, Wang Y, Zhao Y (2016) Synchronization of complex dynamical networks on time scales via Wirtinger-based inequality. Neurocomputing 216:143\u2013149. https:\/\/doi.org\/10.1016\/j.neucom.2016.07.031","journal-title":"Neurocomputing"},{"key":"10820_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.nahs.2020.100903","volume":"37","author":"B Wang","year":"2020","unstructured":"Wang B, Zhang Y, Zhang B (2020) Exponential synchronization of nonlinear complex networks via intermittent pinning control on time scales. Nonlinear Anal Hybrid Syst 37:100903. https:\/\/doi.org\/10.1016\/j.nahs.2020.100903","journal-title":"Nonlinear Anal Hybrid Syst"},{"issue":"2","key":"10820_CR46","doi-asserted-by":"publisher","first-page":"878","DOI":"10.1007\/s12555-020-0041-5","volume":"19","author":"FD Kong","year":"2020","unstructured":"Kong FD, Sun JP (2020) Pinning synchronization of complex dynamical networks on time scales. Int J Control Autom Syst 19(2):878\u2013888. https:\/\/doi.org\/10.1007\/s12555-020-0041-5","journal-title":"Int J Control Autom Syst"},{"key":"10820_CR47","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.nahs.2019.02.005","volume":"33","author":"Z Huang","year":"2019","unstructured":"Huang Z, Cao J, Li J, Bin H (2019) Quasi-synchronization of neural networks with parameter mismatches and delayed impulsive controller on time scales. Nonlinear Anal Hybrid Syst 33:104\u2013115. https:\/\/doi.org\/10.1016\/j.nahs.2019.02.005","journal-title":"Nonlinear Anal Hybrid Syst"},{"issue":"32","key":"10820_CR48","doi-asserted-by":"publisher","first-page":"23649","DOI":"10.1007\/s00521-023-08980-5","volume":"35","author":"V Kumar","year":"2023","unstructured":"Kumar V, Heiland J, Benner P (2023) Projective lag quasi-synchronization of coupled systems with mixed delays and parameter mismatch: a unified theory. Neural Comput Appl 35(32):23649\u201323665. https:\/\/doi.org\/10.1007\/s00521-023-08980-5","journal-title":"Neural Comput Appl"},{"issue":"1","key":"10820_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1687-1847-2014-317","volume":"2014","author":"K Zhao","year":"2014","unstructured":"Zhao K (2014) Global robust exponential synchronization of BAM recurrent FNNs with infinite distributed delays and diffusion terms on time scales. Adv Differ Equ 2014(1):1\u201325. https:\/\/doi.org\/10.1186\/1687-1847-2014-317","journal-title":"Adv Differ Equ"},{"key":"10820_CR50","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.neunet.2020.06.020","volume":"130","author":"Q Xiao","year":"2020","unstructured":"Xiao Q, Huang T (2020) Stability of delayed inertial neural networks on time scales: A unified matrix-measure approach. Neural Netw 130:33\u201338. https:\/\/doi.org\/10.1016\/j.neunet.2020.06.020","journal-title":"Neural Netw"},{"key":"10820_CR51","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s11063-023-11231-2","volume":"130","author":"V Kumar","year":"2023","unstructured":"Kumar V, Heiland J, Benner P (2023) Exponential lag synchronization of Cohen-Grossberg neural networks with discrete and distributed delays on time scales. Neural Process Lett 130:33\u201338. https:\/\/doi.org\/10.1007\/s11063-023-11231-2","journal-title":"Neural Process Lett"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10820-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10820-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10820-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T13:56:59Z","timestamp":1741269419000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10820-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,13]]},"references-count":51,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["10820"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10820-z","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,13]]},"assertion":[{"value":"21 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}