{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:15:09Z","timestamp":1775578509418,"version":"3.50.1"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"30","license":[{"start":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T00:00:00Z","timestamp":1691971200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T00:00:00Z","timestamp":1691971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173176"],"award-info":[{"award-number":["62173176"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61863028"],"award-info":[{"award-number":["61863028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81660299"],"award-info":[{"award-number":["81660299"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61503177"],"award-info":[{"award-number":["61503177"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Department of Jiangxi Province of China","award":["2020ABC03A39"],"award-info":[{"award-number":["2020ABC03A39"]}]},{"name":"Science and Technology Department of Jiangxi Province of China","award":["20161ACB21007"],"award-info":[{"award-number":["20161ACB21007"]}]},{"name":"Science and Technology Department of Jiangxi Province of China","award":["20171BBE50071"],"award-info":[{"award-number":["20171BBE50071"]}]},{"name":"Science and Technology Department of Jiangxi Province of China","award":["20171BAB202033"],"award-info":[{"award-number":["20171BAB202033"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s00521-023-08895-1","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T13:02:10Z","timestamp":1692018130000},"page":"22577-22593","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A novel varying-parameter periodic rhythm neural network for solving time-varying matrix equation in finite energy noise environment and its application to robot arm"],"prefix":"10.1007","volume":"35","author":[{"given":"Chunquan","family":"Li","sequence":"first","affiliation":[]},{"given":"Boyu","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Qingling","family":"Ou","sequence":"additional","affiliation":[]},{"given":"Qianqian","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chong","family":"Yue","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8022-5565","authenticated-orcid":false,"given":"Limin","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Zhijun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Junzhi","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Peter X.","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,8,14]]},"reference":[{"issue":"3\u20135","key":"8895_CR1","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1016\/j.jsv.2009.02.020","volume":"324","author":"S Brahma","year":"2009","unstructured":"Brahma S, Datta B (2009) An optimization approach for minimum norm and robust partial quadratic eigenvalue assignment problems for vibrating structures. J Sound Vib 324(3\u20135):471\u2013489","journal-title":"J Sound Vib"},{"issue":"1","key":"8895_CR2","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1137\/S0895479894273687","volume":"17","author":"D Calvetti","year":"1996","unstructured":"Calvetti D, Reichel L (1996) Application of adi iterative methods to the restoration of noisy images. SIAM J Matrix Anal Appl 17(1):165\u2013186","journal-title":"SIAM J Matrix Anal Appl"},{"issue":"1","key":"8895_CR3","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1109\/TIP.2015.2499698","volume":"25","author":"V Papyan","year":"2015","unstructured":"Papyan V, Elad M (2015) Multi-scale patch-based image restoration. IEEE Trans Image Process 25(1):249\u2013261","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"8895_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TMI.2016.2564989","volume":"36","author":"F Knoll","year":"2016","unstructured":"Knoll F, Holler M, Koesters T, Otazo R, Bredies K, Sodickson DK (2016) Joint mr-pet reconstruction using a multi-channel image regularizer. IEEE Trans Med Imag 36(1):1\u201316","journal-title":"IEEE Trans Med Imag"},{"key":"8895_CR5","doi-asserted-by":"crossref","unstructured":"Ding B, Wen G, Ma C, Yang X (2017) Evaluation of target segmentation on sar target recognition. In: 2017 4th International Conference on Information, Cybernetics and Computational Social Systems (ICCSS), pp. 663\u2013667 . IEEE","DOI":"10.1109\/ICCSS.2017.8091497"},{"key":"8895_CR6","doi-asserted-by":"publisher","first-page":"43892","DOI":"10.1109\/ACCESS.2018.2863745","volume":"6","author":"X Chen","year":"2018","unstructured":"Chen X, Chen B, Guan J, Huang Y, He Y (2018) Space-range-doppler focus-based low-observable moving target detection using frequency diverse array mimo radar. IEEE Access 6:43892\u201343904","journal-title":"IEEE Access"},{"key":"8895_CR7","doi-asserted-by":"crossref","unstructured":"Ahmad AS (2017) Brain inspired cognitive artificial intelligence for knowledge extraction and intelligent instrumentation system. In: 2017 International Symposium on Electronics and Smart Devices (ISESD), pp. 352\u2013356. IEEE","DOI":"10.1109\/ISESD.2017.8253363"},{"key":"8895_CR8","unstructured":"Park J-H, Uhm T-Y, Bae G-D, Choi Y-H (2018) Stability evaluation of outdoor unmanned security robot in terrain information. In: 2018 18th International Conference on Control, Automation and Systems (ICCAS), pp. 955\u2013957. IEEE"},{"key":"8895_CR9","doi-asserted-by":"crossref","unstructured":"Lee J-W, Park G-T, Shin J-S, Woo J-W (2017) Industrial robot calibration method using denavit-hatenberg parameters. In: 2017 17th International Conference on Control, Automation and Systems (ICCAS), pp. 1834\u20131837. IEEE","DOI":"10.23919\/ICCAS.2017.8204265"},{"issue":"21","key":"8895_CR10","doi-asserted-by":"publisher","first-page":"14231","DOI":"10.1007\/s00521-021-06068-6","volume":"33","author":"Z Ma","year":"2021","unstructured":"Ma Z, Yu S, Han Y, Guo D (2021) Zeroing neural network for bound-constrained time-varying nonlinear equation solving and its application to mobile robot manipulators. Neural Comput Appl 33(21):14231\u201314245","journal-title":"Neural Comput Appl"},{"issue":"9","key":"8895_CR11","doi-asserted-by":"publisher","first-page":"4879","DOI":"10.1007\/s00521-018-03986-w","volume":"31","author":"P Miao","year":"2019","unstructured":"Miao P, Wu D, Shen Y, Zhang Z (2019) Discrete-time neural network with two classes of bias noises for solving time-variant matrix inversion and application to robot tracking. Neural Comput Appl 31(9):4879\u20134890","journal-title":"Neural Comput Appl"},{"issue":"23","key":"8895_CR12","doi-asserted-by":"publisher","first-page":"21035","DOI":"10.1007\/s00521-022-07581-y","volume":"34","author":"Z Song","year":"2022","unstructured":"Song Z, Lu Z, Wu J, Xiao X, Wang G (2022) Improved znd model for solving dynamic linear complex matrix equation and its application. Neural Comput Appl 34(23):21035\u201321048","journal-title":"Neural Comput Appl"},{"issue":"9","key":"8895_CR13","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1145\/361573.361582","volume":"15","author":"RH Bartels","year":"1972","unstructured":"Bartels RH, Stewart GW (1972) Solution of the matrix equation ax+ xb= c [f4]. Commun ACM 15(9):820\u2013826","journal-title":"Commun ACM"},{"issue":"8","key":"8895_CR14","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1109\/TAC.2005.852558","volume":"50","author":"F Ding","year":"2005","unstructured":"Ding F, Chen T (2005) Gradient based iterative algorithms for solving a class of matrix equations. IEEE Trans Automat Control 50(8):1216\u20131221","journal-title":"IEEE Trans Automat Control"},{"key":"8895_CR15","doi-asserted-by":"crossref","unstructured":"Zhang H, Yin H (2017) On the best convergence factors of iterative methods of matrix equations based on the gradient and least squares searches. In: 2017 36th Chinese Control Conference (CCC), pp. 111\u2013115 . IEEE","DOI":"10.23919\/ChiCC.2017.8027330"},{"key":"8895_CR16","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/s11063-012-9241-1","volume":"37","author":"S Li","year":"2013","unstructured":"Li S, Chen S, Liu B (2013) Accelerating a recurrent neural network to finite-time convergence for solving time-varying sylvester equation by using a sign-bi-power activation function. Neural Process Lett 37:189\u2013205","journal-title":"Neural Process Lett"},{"key":"8895_CR17","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.neucom.2016.05.010","volume":"207","author":"M Mao","year":"2016","unstructured":"Mao M, Li J, Jin L, Li S, Zhang Y (2016) Enhanced discrete-time zhang neural network for time-variant matrix inversion in the presence of bias noises. Neurocomputing 207:220\u2013230","journal-title":"Neurocomputing"},{"issue":"8","key":"8895_CR18","doi-asserted-by":"publisher","first-page":"5114","DOI":"10.1109\/TSMC.2021.3115555","volume":"52","author":"Q Zuo","year":"2021","unstructured":"Zuo Q, Li K, Xiao L, Wang Y, Li K (2021) On generalized zeroing neural network under discrete and distributed time delays and its application to dynamic lyapunov equation. IEEE Trans Syst Man Cybernet Syst 52(8):5114\u20135126","journal-title":"IEEE Trans Syst Man Cybernet Syst"},{"key":"8895_CR19","doi-asserted-by":"crossref","unstructured":"Madankan A (2010) Recurrent neural network for solving linear matrix equation. In: 2010 International Conference on Electronics and Information Engineering, vol. 2, pp. 2\u201370. IEEE","DOI":"10.1109\/ICEIE.2010.5559717"},{"issue":"3","key":"8895_CR20","doi-asserted-by":"publisher","first-page":"1604","DOI":"10.1109\/TII.2020.2989173","volume":"17","author":"L Xiao","year":"2020","unstructured":"Xiao L, Zhang Y, Dai J, Zuo Q, Wang S (2020) Comprehensive analysis of a new varying parameter zeroing neural network for time varying matrix inversion. IEEE Trans Ind Inform 17(3):1604\u20131613","journal-title":"IEEE Trans Ind Inform"},{"key":"8895_CR21","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1016\/j.neunet.2017.11.011","volume":"98","author":"L Xiao","year":"2018","unstructured":"Xiao L, Liao B, Li S, Chen K (2018) Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations. Neural Netw 98:102\u2013113","journal-title":"Neural Netw"},{"key":"8895_CR22","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/s00521-020-05617-9","volume":"35","author":"J Gong","year":"2021","unstructured":"Gong J, Jin J (2021) A better robustness and fast convergence zeroing neural network for solving dynamic nonlinear equations. Neural Comput Appl 35:77\u201387","journal-title":"Neural Comput Appl"},{"issue":"11","key":"8895_CR23","doi-asserted-by":"publisher","first-page":"12514","DOI":"10.1109\/TCYB.2021.3071764","volume":"52","author":"Y Luo","year":"2021","unstructured":"Luo Y, Deng X, Wu J, Liu Y, Zhang Z (2021) A new finite-time circadian rhythms learning network for solving nonlinear and nonconvex optimization problems with periodic noises. IEEE Trans Cybernet 52(11):12514\u201312524","journal-title":"IEEE Trans Cybernet"},{"issue":"12","key":"8895_CR24","doi-asserted-by":"publisher","first-page":"2615","DOI":"10.1109\/TNNLS.2015.2497715","volume":"27","author":"L Jin","year":"2015","unstructured":"Jin L, Zhang Y, Li S (2015) Integration-enhanced zhang neural network for real-time-varying matrix inversion in the presence of various kinds of noises. IEEE Trans Neural Netw Learn Syst 27(12):2615\u20132627","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8895_CR25","doi-asserted-by":"crossref","unstructured":"Wang S, Dai S, Wang K (2015) Gradient-based neural network for online solution of lyapunov matrix equation with li activation function. In: 4th International Conference on Information Technology and Management Innovation, pp. 955\u2013959. Atlantis Press","DOI":"10.2991\/icitmi-15.2015.161"},{"issue":"4","key":"8895_CR26","doi-asserted-by":"publisher","first-page":"2495","DOI":"10.1016\/j.apm.2012.06.022","volume":"37","author":"C Yi","year":"2013","unstructured":"Yi C, Chen Y, Lan X (2013) Comparison on neural solvers for the lyapunov matrix equation with stationary & nonstationary coefficients. Appl Math Model 37(4):2495\u20132502","journal-title":"Appl Math Model"},{"key":"8895_CR27","doi-asserted-by":"crossref","unstructured":"Yan J, Jin L, Zhang R, Li H, Zhang J, Lu H (2019) Zeroing-type recurrent neural network for solving time-dependent lyapunov equation with noise rejection. In: 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS), pp. 366\u2013371 . IEEE","DOI":"10.1109\/DDCLS.2019.8908866"},{"key":"8895_CR28","doi-asserted-by":"crossref","unstructured":"Xiao L, Liao B, Luo J, Ding L (2017) A convergence-enhanced gradient neural network for solving sylvester equation. In: 2017 36th Chinese Control Conference (CCC), pp. 3910\u20133913. IEEE","DOI":"10.23919\/ChiCC.2017.8027968"},{"issue":"1","key":"8895_CR29","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.camwa.2012.08.017","volume":"55","author":"J Wang","year":"1993","unstructured":"Wang J (1993) A recurrent neural network for real-time matrix inversion. Appl Math Comput 55(1):89\u2013100","journal-title":"Appl Math Comput"},{"issue":"6","key":"8895_CR30","doi-asserted-by":"publisher","first-page":"3629","DOI":"10.1109\/TSMC.2019.2930646","volume":"51","author":"L Xiao","year":"2019","unstructured":"Xiao L, Zhang Y, Dai J, Li J, Li W (2019) New noise-tolerant znn models with predefined-time convergence for time-variant sylvester equation solving. IEEE Trans Syst Man Cybernet Syst 51(6):3629\u20133640","journal-title":"IEEE Trans Syst Man Cybernet Syst"},{"issue":"6","key":"8895_CR31","doi-asserted-by":"publisher","first-page":"1477","DOI":"10.1109\/TNN.2005.857946","volume":"16","author":"Y Zhang","year":"2005","unstructured":"Zhang Y, Ge SS (2005) Design and analysis of a general recurrent neural network model for time-varying matrix inversion. IEEE Trans Neural Netw 16(6):1477\u20131490","journal-title":"IEEE Trans Neural Netw"},{"key":"8895_CR32","doi-asserted-by":"crossref","unstructured":"Xiao L, Ding S, Mao M, Zhang Y, Liao B (2014) Finite-time convergence analysis and verification of improved znn for real-time matrix inversion. In: 2014 4th IEEE International Conference on Information Science and Technology, pp. 286\u2013289. IEEE","DOI":"10.1109\/ICIST.2014.6920385"},{"issue":"11","key":"8895_CR33","doi-asserted-by":"publisher","first-page":"3135","DOI":"10.1109\/TCYB.2017.2760883","volume":"48","author":"Z Zhang","year":"2018","unstructured":"Zhang Z, Zheng L, Weng J, Mao Y, Lu W, Xiao L (2018) A new varying-parameter recurrent neural-network for online solution of time-varying sylvester equation. IEEE Trans Cybernet 48(11):3135\u20133148","journal-title":"IEEE Trans Cybernet"},{"issue":"4","key":"8895_CR34","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1109\/TNNLS.2020.3042761","volume":"33","author":"L Xiao","year":"2020","unstructured":"Xiao L, He Y, Dai J, Liu X, Liao B, Tan H (2020) A variable-parameter noise-tolerant zeroing neural network for time-variant matrix inversion with guaranteed robustness. IEEE Trans Neural Netw Learn Syst 33(4):1535\u20131545","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"5","key":"8895_CR35","doi-asserted-by":"publisher","first-page":"2605","DOI":"10.1109\/TII.2018.2867169","volume":"15","author":"L Xiao","year":"2018","unstructured":"Xiao L, Li S, Lin F-J, Tan Z, Khan AH (2018) Zeroing neural dynamics for control design: comprehensive analysis on stability, robustness, and convergence speed. IEEE Trans Ind Inform 15(5):2605\u20132616","journal-title":"IEEE Trans Ind Inform"},{"issue":"10","key":"8895_CR36","doi-asserted-by":"publisher","first-page":"6840","DOI":"10.1109\/TII.2021.3135383","volume":"18","author":"L Xiao","year":"2021","unstructured":"Xiao L, Song W, Li X, Jia L, Sun J, Wang Y (2021) Design and analysis of a noise-resistant znn model for settling time-variant linear matrix inequality in predefined-time. IEEE Trans Ind Inform 18(10):6840\u20136847","journal-title":"IEEE Trans Ind Inform"},{"issue":"3","key":"8895_CR37","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1109\/TCDS.2019.2948066","volume":"12","author":"Z Zhang","year":"2019","unstructured":"Zhang Z, Deng X, Kong L, Li S (2019) A circadian rhythms learning network for resisting cognitive periodic noises of time-varying dynamic system and applications to robots. IEEE Trans Cognit Dev Syst 12(3):575\u2013587","journal-title":"IEEE Trans Cognit Dev Syst"},{"issue":"12","key":"8895_CR38","doi-asserted-by":"publisher","first-page":"4194","DOI":"10.1109\/TCYB.2018.2859751","volume":"49","author":"Y Zhang","year":"2018","unstructured":"Zhang Y, Li S, Kadry S, Liao B (2018) Recurrent neural network for kinematic control of redundant manipulators with periodic input disturbance and physical constraints. IEEE Trans Cybernet 49(12):4194\u20134205","journal-title":"IEEE Trans Cybernet"},{"key":"8895_CR39","doi-asserted-by":"crossref","unstructured":"Lokvenc J, Drtina R (2017) Asynchronous machine set for electrical laboratories part 1: Noise load. In: 2017 European Conference on Electrical Engineering and Computer Science (EECS), pp. 295\u2013299. IEEE","DOI":"10.1109\/EECS.2017.61"},{"key":"8895_CR40","doi-asserted-by":"crossref","unstructured":"Sharma MK, Vig R (2014) Server noise: health hazard and its reduction using active noise control. In: 2014 Recent Advances in Engineering and Computational Sciences (RAECS), pp. 1\u20135. IEEE","DOI":"10.1109\/RAECS.2014.6799628"},{"issue":"6","key":"8895_CR41","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.physrep.2003.10.015","volume":"392","author":"B Lindner","year":"2004","unstructured":"Lindner B, Garc\u0131a-Ojalvo J, Neiman A, Schimansky-Geier L (2004) Effects of noise in excitable systems. Phys Rep 392(6):321\u2013424","journal-title":"Phys Rep"},{"key":"8895_CR42","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/s11571-017-9466-9","volume":"12","author":"J Zhu","year":"2018","unstructured":"Zhu J, Liu X (2018) Measuring spike timing distance in the hindmarsh-rose neurons. Cognit Neurodyn 12:225\u2013234","journal-title":"Cognit Neurodyn"},{"key":"8895_CR43","doi-asserted-by":"publisher","first-page":"2987","DOI":"10.1007\/s00034-014-9784-7","volume":"33","author":"K Zeng","year":"2014","unstructured":"Zeng K, Huang J, Dong M (2014) White gaussian noise energy estimation and wavelet multi-threshold de-noising for heart sound signals. Circuits Syst Signal Process 33:2987\u20133002","journal-title":"Circuits Syst Signal Process"},{"issue":"9","key":"8895_CR44","doi-asserted-by":"publisher","first-page":"3892","DOI":"10.1109\/TCOMM.2017.2710312","volume":"65","author":"M Wen","year":"2017","unstructured":"Wen M, Basar E, Li Q, Zheng B, Zhang M (2017) Multiple-mode orthogonal frequency division multiplexing with index modulation. IEEE Trans Commun 65(9):3892\u20133906","journal-title":"IEEE Trans Commun"},{"key":"8895_CR45","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.jnca.2017.04.012","volume":"90","author":"TP Vieira","year":"2017","unstructured":"Vieira TP, Ten\u00f3rio DF, da Costa JPC, de Freitas EP, Del Galdo G, de Sousa J\u00fanior RT (2017) Model order selection and eigen similarity based framework for detection and identification of network attacks. J Netw Comput Appl 90:26\u201341","journal-title":"J Netw Comput Appl"},{"key":"8895_CR46","doi-asserted-by":"crossref","unstructured":"Lv J, Wang F (2015) Image laplace denoising based on sparse representation. In: 2015 International Conference on Computational Intelligence and Communication Networks (CICN), pp. 373\u2013377. IEEE","DOI":"10.1109\/CICN.2015.80"},{"key":"8895_CR47","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1007\/s11082-013-9793-y","volume":"46","author":"Z Wang","year":"2014","unstructured":"Wang Z, Chang J, Zhang S, Sun B, Jiang S, Luo S, Jia C, Liu Y, Liu X, Lv G et al (2014) An adaptive rayleigh noise elimination method in raman distributed temperature sensors using anti-stokes signal only. Opt Quant Electron 46:821\u2013827","journal-title":"Opt Quant Electron"},{"key":"8895_CR48","doi-asserted-by":"publisher","first-page":"4237","DOI":"10.1007\/s12652-020-01818-1","volume":"12","author":"A Sai Suneel","year":"2021","unstructured":"Sai Suneel A, Shiyamala S (2021) Peak detection based energy detection of a spectrum under rayleigh fading noise environment. J Ambient Intel Human Comput 12:4237\u20134245","journal-title":"J Ambient Intel Human Comput"},{"issue":"10","key":"8895_CR49","doi-asserted-by":"publisher","first-page":"4791","DOI":"10.1109\/TNNLS.2017.2770172","volume":"29","author":"S Li","year":"2017","unstructured":"Li S, Zhou M, Luo X (2017) Modified primal-dual neural networks for motion control of redundant manipulators with dynamic rejection of harmonic noises. IEEE Trans Neural Netw Learn Syst 29(10):4791\u20134801","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8895_CR50","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.neucom.2023.02.033","volume":"534","author":"Z Zhang","year":"2023","unstructured":"Zhang Z, Ye L, Chen B, Luo Y (2023) An anti-interference dynamic integral neural network for solving the time-varying linear matrix equation with periodic noises. Neurocomputing 534:29\u201344","journal-title":"Neurocomputing"},{"issue":"9","key":"8895_CR51","doi-asserted-by":"publisher","first-page":"2449","DOI":"10.1109\/TPEL.2011.2107334","volume":"26","author":"L Shen","year":"2011","unstructured":"Shen L, Wu J, Yang S (2011) Initial position estimation in srm using bootstrap circuit without predefined inductance parameters. IEEE Trans Power Electron 26(9):2449\u20132456","journal-title":"IEEE Trans Power Electron"},{"issue":"24","key":"8895_CR52","doi-asserted-by":"publisher","first-page":"245202","DOI":"10.1088\/1751-8113\/43\/24\/245202","volume":"43","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Ruan G, Li K, Yang Y (2010) Robustness analysis of the Zhang neural network for online time-varying quadratic optimization. J Phys A Math Theor 43(24):245202","journal-title":"J Phys A Math Theor"},{"key":"8895_CR53","doi-asserted-by":"crossref","unstructured":"Guo L, Li Y, Wang T, Wang H, Wang H (2017) Analysis and detection on noise characteristics of ac power transmission and transformation project in different voltage levels. In: 2017 2nd International Conference on Power and Renewable Energy (ICPRE), pp. 336\u2013340. IEEE","DOI":"10.1109\/ICPRE.2017.8390554"},{"key":"8895_CR54","doi-asserted-by":"crossref","unstructured":"Girgis RS, Bernesjo M, Anger J (2009) Comprehensive analysis of load noise of power transformers. In: 2009 IEEE Power & Energy Society General Meeting, pp. 1\u20137. IEEE","DOI":"10.1109\/PES.2009.5275883"},{"issue":"4","key":"8895_CR55","first-page":"719","volume":"27","author":"Chuangxia Huang","year":"2022","unstructured":"Huang Chuangxia, Liu Bingwen, Yang Hedi, Cao Jinde (2022) Positive almost periodicity on SICNNs incorporating mixed delays and D operator. Nonlinear Anal Model Control 27(4):719\u2013739","journal-title":"Nonlinear Anal Model Control"},{"key":"8895_CR56","doi-asserted-by":"crossref","unstructured":"Wang W (2022) Further results on mean-square exponential Input-to-State stability of stochastic delayed Cohen-Grossberg neural networks. Neural Processing Letters, 1\u201313","DOI":"10.1080\/0952813X.2023.2165725"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08895-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08895-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08895-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,16]],"date-time":"2023-09-16T15:10:20Z","timestamp":1694877020000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08895-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,14]]},"references-count":56,"journal-issue":{"issue":"30","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["8895"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08895-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,14]]},"assertion":[{"value":"21 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2023","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 known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}