{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T16:40:19Z","timestamp":1782146419497,"version":"3.54.5"},"reference-count":152,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T00:00:00Z","timestamp":1749686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62466019"],"award-info":[{"award-number":["62466019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Neurodynamics is recognized as a powerful tool for addressing various problems in engineering, control, and intelligent systems. Over the past decade, neurodynamics-based methods and models have been rapidly developed, particularly in emerging areas such as neural computation and multi-agent systems. In this paper, we provide a brief survey of neurodynamics applied to computation and multi-agent systems. Specifically, we highlight key models and approaches related to time-varying computation, as well as cooperative and competitive behaviors in multi-agent systems. Furthermore, we discuss current challenges, potential opportunities, and promising future directions in this evolving field.<\/jats:p>","DOI":"10.3390\/sym17060936","type":"journal-article","created":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T07:44:23Z","timestamp":1749714263000},"page":"936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Survey of Neurodynamic Methods for Control and Computation in Multi-Agent Systems"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8208-9656","authenticated-orcid":false,"given":"Vasilios N.","family":"Katsikis","sequence":"first","affiliation":[{"name":"Department of Economics, National and Kapodistrian University of Athens, 10559 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9036-2723","authenticated-orcid":false,"given":"Bolin","family":"Liao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Jishou University, Jishou 416000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4788-5067","authenticated-orcid":false,"given":"Cheng","family":"Hua","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Jishou University, Jishou 416000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2798","DOI":"10.1109\/JBHI.2020.3019505","article-title":"Adaptive feature selection guided deep forest for COVID-19 classification with chest CT","volume":"24","author":"Sun","year":"2020","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, Y., and Khan, A.H. (2023, January 10\u201313). Undetectable attack to deep neural networks without using model parameters. Proceedings of the International Conference on Intelligent Computing, Zhengzhou, China.","DOI":"10.1007\/978-981-99-4742-3_4"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e1441","DOI":"10.7717\/peerj-cs.1441","article-title":"A deep learning-based approach for emotional analysis of sports dance","volume":"9","author":"Sun","year":"2023","journal-title":"PeerJ Comput. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s11063-022-10900-y","article-title":"Heavy-head sampling for fast imitation learning of machine learning based combinatorial auction solver","volume":"55","author":"Peng","year":"2023","journal-title":"Neural Process. Lett."},{"key":"ref_5","first-page":"15","article-title":"Using imbalanced triangle synthetic data for machine learning anomaly detection","volume":"58","author":"Luo","year":"2019","journal-title":"CMC Comput. Mater. Contin."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"106339","DOI":"10.1016\/j.neunet.2024.106339","article-title":"DCDLN: A densely connected convolutional dynamic learning network for malaria disease diagnosis","volume":"176","author":"Zhang","year":"2024","journal-title":"Neural Netw."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Chen, L., Jin, L., and Shang, M. (2024). Efficient loss landscape reshaping for convolutional neural networks. IEEE Trans. Neural Netw., in press.","DOI":"10.1109\/TNNLS.2024.3462516"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6567","DOI":"10.1007\/s10462-022-10161-0","article-title":"Modeling, reasoning, and application of fuzzy Petri net model: A survey","volume":"55","author":"Jiang","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2450022","DOI":"10.1142\/S021969132450022X","article-title":"Improved-equivalent-input-disturbance-based preview repetitive control for Takagi-Sugeno fuzzy system with state delay","volume":"22","author":"Luo","year":"2024","journal-title":"Int. J. Wavelets Multiresolut. Inf. Process."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Qu, C., Zhang, L., Li, J., Deng, F., Tang, Y., Zeng, X., and Peng, X. (2021). Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning. Brief. Bioinform., 22.","DOI":"10.1093\/bib\/bbab097"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ou, Y., Qin, F., Zhou, K.Q., Yin, P.F., Mo, L.P., and Mohd Zain, A. (2024). An improved grey wolf optimizer with multi-strategies coverage in wireless sensor networks. Symmetry, 16.","DOI":"10.3390\/sym16030286"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.asoc.2016.05.011","article-title":"A label based ant colony algorithm for heterogeneous vehicle routing with mixed backhaul","volume":"47","author":"Wu","year":"2016","journal-title":"Appl. Soft. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Huang, Z., Zhang, Z., Hua, C., Liao, B., and Li, S. (2024). Leveraging enhanced egret swarm optimization algorithm and artificial intelligence-driven prompt strategies for portfolio selection. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-77925-2"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"17923","DOI":"10.1007\/s00500-023-09080-1","article-title":"Improved differential evolution with dynamic mutation parameters","volume":"27","author":"Lin","year":"2023","journal-title":"Soft Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"101126","DOI":"10.1016\/j.swevo.2022.101126","article-title":"Harmony search algorithm and related variants: A systematic review","volume":"74","author":"Qin","year":"2022","journal-title":"Swarm Evol. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1574","DOI":"10.1631\/FITEE.2200334","article-title":"A modified harmony search algorithm and its applications in weighted fuzzy production rule extraction","volume":"24","author":"Ye","year":"2023","journal-title":"Front. Inform. Technol. Electron. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"10595","DOI":"10.1007\/s00500-021-05991-z","article-title":"Convergence analysis of beetle antennae search algorithm and its applications","volume":"25","author":"Zhang","year":"2021","journal-title":"Soft Comput."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liu, J., Qu, C., Zhang, L., Tang, Y., Li, J., Feng, H., and Peng, X. (2023). A new hybrid algorithm for three-stage gene selection based on whale optimization. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-30862-y"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e1229","DOI":"10.7717\/peerj-cs.1229","article-title":"A novel hybrid algorithm based on Harris Hawks for tumor feature gene selection","volume":"13","author":"Liu","year":"2023","journal-title":"PeerJ Comput. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"128810","DOI":"10.1016\/j.neucom.2024.128810","article-title":"Finite-time-convergent support vector neural dynamics for classification","volume":"617","author":"Liu","year":"2025","journal-title":"Neurocomputing"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8166","DOI":"10.1109\/TNNLS.2024.3437676","article-title":"Convolutional dynamically convergent differential neural network for brain signal classification","volume":"36","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"14459","DOI":"10.1109\/TMC.2024.3443992","article-title":"A localization algorithm for underwater acoustic sensor networks with improved newton iteration and simplified Kalman filter","volume":"23","author":"Liu","year":"2024","journal-title":"IEEE Trans. Mobile Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"102261","DOI":"10.1016\/j.neunet.2024.106621","article-title":"Joint computation offloading and resource allocation for end-edge collaboration in internet of vehicles via multi-agent reinforcement learning","volume":"179","author":"Wang","year":"2024","journal-title":"Neural Netw."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"18052","DOI":"10.1109\/TNNLS.2023.3311169","article-title":"Neural networks for portfolio analysis in high-frequency trading","volume":"35","author":"Cao","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5429","DOI":"10.1109\/TAC.2017.2694547","article-title":"Distributed biased min-consensus with applications to shortest path planning","volume":"62","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.automatica.2017.08.014","article-title":"Perturbing consensus for complexity: A finite-time discrete biased min-consensus under time-delay and asynchronism","volume":"85","author":"Zhang","year":"2017","journal-title":"Automatica"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1007\/s11071-017-3553-7","article-title":"A type of biased consensus-based distributed neural network for path planning","volume":"89","author":"Zhang","year":"2017","journal-title":"Nonlinear Dyn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"6297","DOI":"10.1109\/TCYB.2024.3436021","article-title":"Cerebellum-inspired learning and control scheme for redundant manipulators at joint velocity level","volume":"54","author":"Jin","year":"2024","journal-title":"IEEE Trans. Cybern."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3534","DOI":"10.1109\/TNNLS.2024.3351674","article-title":"Novel snap-layer MMPC scheme via neural dynamics equivalency and solver for redundant robot arms with five-layer physical limits","volume":"36","author":"Tang","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1007\/s00500-020-05139-5","article-title":"A self-adapting hierarchical actions and structures joint optimization framework for automatic design of robotic and animation skeletons","volume":"25","author":"Xiang","year":"2021","journal-title":"Soft Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4194","DOI":"10.1109\/TCYB.2018.2859751","article-title":"Recurrent neural network for kinematic control of redundant manipulators with periodic input disturbance and physical constraints","volume":"49","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Cybern."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Xiao, L., Zhang, Y., Liao, B., Zhang, Z., Ding, L., and Jin, L. (2017). A velocity-level bi-criteria optimization scheme for coordinated path tracking of dual robot manipulators using recurrent neural network. Front. Neurobot., 11.","DOI":"10.3389\/fnbot.2017.00047"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Cao, Z., and Li, X. (2024). Neural dynamic fault-tolerant scheme for collaborative motion planning of dual-redundant robot manipulators. IEEE Trans. Neural Netw. Learn. Syst., in press.","DOI":"10.1109\/TNNLS.2024.3466296"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1993","DOI":"10.1007\/s11063-019-09983-x","article-title":"Improved gradient neural networks for solving Moore-Penrose inverse of full-rank matrix","volume":"50","author":"Lv","year":"2019","journal-title":"Neural Process. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1049\/cit2.12161","article-title":"Double integral-enhanced Zeroing neural network with linear noise rejection for time-varying matrix inverse","volume":"9","author":"Liao","year":"2023","journal-title":"CAAI Trans. Intell. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2817","DOI":"10.1109\/TSMC.2016.2523917","article-title":"From Davidenko method to Zhang dynamics for nonlinear equation systems solving","volume":"47","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_37","first-page":"882","article-title":"Recurrent neural network With scheduled varying gain for solving time-varying QP","volume":"71","author":"Fu","year":"2024","journal-title":"IEEE Trans. Circuits Syst. II Express Briefs"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.neunet.2022.01.005","article-title":"Finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms: A non-separation approach","volume":"148","author":"Long","year":"2022","journal-title":"Neural Netw."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.26599\/TST.2024.9010120","article-title":"Novel Zeroing Neural Network for Time-Varying Matrix Pseudoinversion in the Presence of Linear Noises","volume":"30","author":"Li","year":"2025","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e70042","DOI":"10.1111\/coin.70042","article-title":"Real-Time Solutions for Dynamic Complex Matrix Inversion and Chaotic Control Using ODE-Based Neural Computing Methods","volume":"41","author":"Hua","year":"2025","journal-title":"Comput. Intell."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"5795","DOI":"10.1109\/TNNLS.2024.3377433","article-title":"Distributed dynamic task allocation for moving target tracking of networked mobile robots using k-WTA network","volume":"36","author":"Liu","year":"2025","journal-title":"Trans. Neural Netw. Learn. Syst."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Deng, Q., and Zhang, Y. (2021, January 18\u201322). Distributed near-optimal consensus of double-integrator multi-agent systems with input constraints. Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China.","DOI":"10.1109\/IJCNN52387.2021.9533377"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3047","DOI":"10.1109\/TCYB.2020.3022653","article-title":"Distributed estimation of algebraic connectivity","volume":"52","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.ipl.2018.10.004","article-title":"Nonlinear gradient neural network for solving system of linear equations","volume":"142","author":"Xiao","year":"2019","journal-title":"Inf. Process. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1360","DOI":"10.1080\/00207721.2024.2425952","article-title":"A survey on zeroing neural dynamics: Models, theories, and applications","volume":"56","author":"Li","year":"2025","journal-title":"Int. J. Syst. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.neucom.2018.01.002","article-title":"Robot manipulator control using neural networks: A survey","volume":"285","author":"Jin","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"e8218","DOI":"10.1002\/cpe.8218","article-title":"A noise-tolerant fuzzy-type zeroing neural network for robust synchronization of chaotic systems","volume":"36","author":"Liu","year":"2024","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"6978","DOI":"10.1109\/TIE.2016.2590379","article-title":"Modified ZNN for time-varying quadratic programming with inherent tolerance to noises and its application to kinematic redundancy resolution of robot manipulators","volume":"63","author":"Jin","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"115989","DOI":"10.1016\/j.measurement.2024.115989","article-title":"A novel adaptive parameter zeroing neural network for the synchronization of complex chaotic systems and its field programmable gate array implementation","volume":"242","author":"Zhao","year":"2025","journal-title":"Measurement"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"11788","DOI":"10.1016\/j.jfranklin.2023.09.009","article-title":"A novel predefined-time noise-tolerant zeroing neural network for solving time-varying generalized linear matrix equations","volume":"360","author":"Li","year":"2023","journal-title":"J. Frankl. Inst."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"4786","DOI":"10.1109\/TSMC.2024.3387023","article-title":"GNN model with robust finite-time convergence for time-varying systems of linear equations","volume":"54","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1109\/TNNLS.2022.3175899","article-title":"GNN Model for time-varying matrix inversion with robust finite-time convergence","volume":"35","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"10919","DOI":"10.1109\/TNNLS.2022.3171715","article-title":"Dynamic Moore\u2013Penrose inversion with unknown derivatives: Gradient neural network approach","volume":"34","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.ins.2022.08.061","article-title":"Improved GNN method with finite-time convergence for time-varying Lyapunov equation","volume":"611","author":"Zhang","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_55","first-page":"1630","article-title":"Finite-time convergent modified Davidenko method for dynamic nonlinear equations","volume":"70","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Circuits Syst. II Exp. Briefs"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1109\/TNN.2002.1031938","article-title":"A recurrent neural network for solving Sylvester equation with time-varying coefficients","volume":"13","author":"Zhang","year":"2002","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.neucom.2019.07.044","article-title":"Design and analysis of new complex zeroing neural network for a set of dynamic complex linear equations","volume":"363","author":"Xiao","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"126883","DOI":"10.1016\/j.neucom.2023.126883","article-title":"Continuous and discrete gradient-Zhang neuronet (GZN) with analyses for time-variant overdetermined linear equation system solving as well as mobile localization applications","volume":"561","author":"Tang","year":"2023","journal-title":"Neurocomputing"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.ipl.2019.03.012","article-title":"Improved Zhang neural network with finite-time convergence for time-varying linear system of equations solving","volume":"147","author":"Lv","year":"2019","journal-title":"Inf. Process. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Ding, L., Xiao, L., Liao, B., Lu, R., and Peng, H. (2017). An improved recurrent neural network for complex-valued systems of linear equation and its application to robotic motion tracking. Front. Neurorobot., 11.","DOI":"10.3389\/fnbot.2017.00045"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1016\/j.neucom.2015.08.031","article-title":"A nonlinearly activated neural dynamics and its finite-time solution to time-varying nonlinear equation","volume":"173","author":"Xiao","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.neucom.2014.09.047","article-title":"Finite-time solution to nonlinear equation using recurrent neural dynamics with a specially-constructed activation function","volume":"151","author":"Xiao","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"3195","DOI":"10.1109\/TCYB.2019.2906263","article-title":"A finite-time convergent and noise-rejection recurrent neural network and its discretization for dynamic nonlinear equations solving","volume":"50","author":"Li","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1049\/cit2.12360","article-title":"Norm-based zeroing neural dynamics for time-variant non-linear equations","volume":"9","author":"Dai","year":"2024","journal-title":"CAAI Trans. Intell. Techonol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.neunet.2019.05.005","article-title":"A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion","volume":"117","author":"Xiao","year":"2019","journal-title":"Neural Netw."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1109\/TAC.2016.2566880","article-title":"Noise-tolerant ZNN models for solving time-varying zero-finding problems: A control-theoretic approach","volume":"62","author":"Jin","year":"2017","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.neucom.2020.02.121","article-title":"New error function designs for finite-time ZNN models with application to dynamic matrix inversion","volume":"402","author":"Xiao","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.tcs.2016.07.024","article-title":"A new design formula exploited for accelerating Zhang neural network and its application to time-varying matrix inversion","volume":"647","author":"Xiao","year":"2016","journal-title":"Theor. Comput. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.neucom.2018.11.071","article-title":"A novel recurrent neural network and its finite-time solution to time-varying complex matrix inversion","volume":"331","author":"Xiao","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1109\/TNNLS.2015.2497715","article-title":"Integration-enhanced Zhang neural network for real-time-varying matrix inversion in the presence of various kinds of noises","volume":"27","author":"Jin","year":"2015","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.1109\/TNNLS.2020.3042761","article-title":"A variable-parameter noise-tolerant zeroing neural network for time-variant matrix inversion with guaranteed robustness","volume":"33","author":"Xiao","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1007\/s00500-018-3119-8","article-title":"Discrete-time noise-tolerant Zhang neural network for dynamic matrix pseudoinversion","volume":"23","author":"Xiang","year":"2019","journal-title":"Soft Comput."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Liao, B., Wang, Y., Li, J., Guo, D., and He, Y. (2022). Harmonic noise-tolerant ZNN for dynamic matrix pseudoinversion and its application to robot manipulator. Front. Neurorobot., 16.","DOI":"10.3389\/fnbot.2022.928636"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.neucom.2018.10.031","article-title":"Bounded Z-type neurodynamics with limited-time convergence and noise tolerance for calculating time-dependent Lyapunov equation","volume":"325","author":"Liao","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.neucom.2018.06.057","article-title":"Wsbp function activated Zhang dynamic with finite-time convergence applied to Lyapunov equation","volume":"314","author":"Lv","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.neucom.2016.02.021","article-title":"A convergence-accelerated Zhang neural network and its solution application to Lyapunov equation","volume":"193","author":"Xiao","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.neunet.2017.11.011","article-title":"Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations","volume":"98","author":"Xiao","year":"2018","journal-title":"Neural Netw."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.neucom.2015.04.070","article-title":"A finite-time convergent neural dynamics for online solution of time-varying linear complex matrix equation","volume":"167","author":"Xiao","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.neucom.2019.01.072","article-title":"A recurrent neural network with predefined-time convergence and improved noise tolerance for dynamic matrix square root finding","volume":"337","author":"Li","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.neucom.2023.01.008","article-title":"A predefined-time and anti-noise varying-parameter ZNN model for solving time-varying complex Stein equations","volume":"526","author":"Xiao","year":"2023","journal-title":"Neurocomputing"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"3135","DOI":"10.1109\/TCYB.2017.2760883","article-title":"A new varying-parameter recurrent neural-network for online solution of time-varying Sylvester equation","volume":"48","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Cybern."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.neunet.2018.05.008","article-title":"Design, verification and robotic application of a novel recurrent neural network for computing dynamic Sylvester equation","volume":"105","author":"Xiao","year":"2018","journal-title":"Neural Netw."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"4874","DOI":"10.1109\/TII.2023.3329640","article-title":"Norm-based finite-time convergent recurrent neural network for dynamic linear inequality","volume":"20","author":"Dai","year":"2024","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"5339","DOI":"10.1109\/TNNLS.2020.2966294","article-title":"Design and comprehensive analysis of a noise-tolerant ZNN model with limited-time convergence for time-dependent nonlinear minimization","volume":"31","author":"Xiao","year":"2020","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"691","DOI":"10.2298\/CSIS160215023L","article-title":"Performance analyses of recurrent neural network models exploited for online time-varying nonlinear optimization","volume":"13","author":"Liu","year":"2016","journal-title":"Comput. Sci. Inform. Syst."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.neucom.2018.01.033","article-title":"A new recurrent neural network with noise-tolerance and finite-time convergence for dynamic quadratic minimization","volume":"285","author":"Xiao","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"3360","DOI":"10.1109\/TNNLS.2019.2891252","article-title":"Computing time-varying quadratic optimization with finite-time convergence and noise tolerance: A unified framework for zeroing neural network","volume":"30","author":"Xiao","year":"2019","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"2413","DOI":"10.1109\/TNNLS.2021.3106640","article-title":"A segmented variable-parameter ZNN for dynamic quadratic minimization with improved convergence and robustness","volume":"34","author":"Xiao","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.asoc.2015.11.023","article-title":"A nonlinearly-activated neurodynamic model and its finite-time solution to equality-constrained quadratic optimization with nonstationary coefficients","volume":"40","author":"Xiao","year":"2016","journal-title":"Appl. Soft. Comput."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1109\/TNNLS.2015.2435014","article-title":"Taylor O(h3) discretization of ZNN models for dynamic equality-constrained quadratic programming with application to manipulators","volume":"27","author":"Liao","year":"2016","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.neucom.2018.07.005","article-title":"A new finite-time varying-parameter convergent-differential neural-network for solving nonlinear and nonconvex optimization problems","volume":"319","author":"Zhang","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"5866","DOI":"10.1109\/TCYB.2024.3398585","article-title":"A novel swarm-exploring neurodynamic network for obtaining global optimal solutions to nonconvex nonlinear programming problems","volume":"54","author":"Luo","year":"2024","journal-title":"IEEE Trans. Cybern."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"128203","DOI":"10.1016\/j.neucom.2024.128203","article-title":"A swarm exploring neural dynamics method for solving convex multi-objective optimization problem","volume":"601","author":"Zhang","year":"2024","journal-title":"Neurocomputing"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"2935","DOI":"10.1109\/TETCI.2024.3369482","article-title":"Collaborative neural solution for time-varying nonconvex optimization with noise rejection","volume":"8","author":"Wei","year":"2024","journal-title":"IEEE Trans. Emerg. Topics Comput. Intell."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1080\/00207721.2022.2141594","article-title":"Adaptive quadratic optimisation with application to kinematic control of redundant robot manipulators","volume":"54","author":"Zhang","year":"2023","journal-title":"Int. J. Syst. Sci."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Jin, L., Liao, B., Liu, M., Xiao, L., Guo, D., and Yan, X. (2017). Different-level simultaneous minimization scheme for fault tolerance of redundant manipulator aided with discrete-time recurrent neural network. Front. Neurobot., 11.","DOI":"10.3389\/fnbot.2017.00050"},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"5901","DOI":"10.1109\/TCYB.2024.3408254","article-title":"Data-driven model predictive control for redundant manipulators with unknown model","volume":"54","author":"Yan","year":"2024","journal-title":"IEEE Trans. Cybern."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Tang, Z., and Zhang, Y.N. (2022). Refined self-motion scheme with zero initial velocities and time-varying physical Limits via Zhang neurodynamics equivalency. Front. Neurobot., 16.","DOI":"10.3389\/fnbot.2022.945346"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"3029","DOI":"10.1109\/TII.2019.2908442","article-title":"A passivity-based approach for kinematic control of manipulators with constraints","volume":"16","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1109\/TII.2017.2737363","article-title":"Velocity-level control with compliance to acceleration-level constraints: A novel scheme for manipulator redundancy resolution","volume":"14","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1109\/TIE.2018.2851960","article-title":"Recurrent-neural-network-based velocity-level redundancy resolution for manipulators subject to a joint acceleration limit","volume":"66","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_102","first-page":"4879","article-title":"Tri-projection neural network for redundant manipulators","volume":"69","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Circuits Syst. II Exp. Briefs"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"4909","DOI":"10.1109\/TIE.2017.2774720","article-title":"Adaptive projection neural network for kinematic control of redundant manipulators with unknown physical parameters","volume":"65","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Zhang, C., Zhang, Y., and Dai, L. (2023, January 20\u201322). Deception-attack-resilient kinematic control of redundant manipulators: A projection neural network approach. Proceedings of the 2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC), Shenzhen, China.","DOI":"10.1109\/CSIS-IAC60628.2023.10364228"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1109\/JAS.2023.123132","article-title":"Kinematic control of serial manipulators under false data injection attack","volume":"10","author":"Zhang","year":"2023","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"5419","DOI":"10.1109\/TNNLS.2018.2802650","article-title":"A neural controller for image-based visual servoing of manipulators with physical constraints","volume":"29","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_107","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, S., Liao, B., Jin, L., and Zheng, L. (2017, January 18\u201320). A recurrent neural network approach for visual servoing of manipulators. Proceedings of the 2017 IEEE International Conference on Information and Automation (ICIA), Macao, China.","DOI":"10.1109\/ICInfA.2017.8078981"},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zheng, Y., Gao, F., and Li, S. (2024). Image-based visual servoing of manipulators with unknown depth: A recurrent neural network approach. IEEE Trans. Neural Netw. Learn. Syst., in press.","DOI":"10.1109\/TNNLS.2024.3454128"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1957","DOI":"10.1109\/TSMC.2017.2703140","article-title":"Time-scale expansion-based approximated optimal control for underactuated systems Using projection neural networks","volume":"48","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"7173","DOI":"10.1109\/TIE.2018.2793233","article-title":"Near-optimal control without solving HJB equations and its applications","volume":"65","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"7453","DOI":"10.1109\/TCYB.2020.3041368","article-title":"Learning and near-optimal control of underactuated surface vessels with periodic disturbances","volume":"52","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Cybern."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"6227","DOI":"10.1109\/TNNLS.2018.2828114","article-title":"Neural network-based model-free adaptive near-optimal tracking control for a class of nonlinear systems","volume":"29","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_113","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, S., Luo, X., and Shang, M.S. (2017, January 14\u201319). A dynamic neural controller for adaptive optimal control of permanent magnet DC motors. Proceedings of the 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, USA.","DOI":"10.1109\/IJCNN.2017.7965939"},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1109\/TCST.2017.2705057","article-title":"Adaptive near-optimal control of uncertain systems with application to underactuated surface vessels","volume":"26","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.arcontrol.2019.01.003","article-title":"Near-optimal control of nonlinear dynamical systems: A brief survey","volume":"47","author":"Zhang","year":"2019","journal-title":"Annu. Rev. Control"},{"key":"ref_116","first-page":"1298","article-title":"Input delay estimation for input-affine dynamical systems based on Taylor expansion","volume":"68","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Circuits Syst. II Express Briefs"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"11436","DOI":"10.1109\/TMC.2024.3397242","article-title":"A distributed competitive and collaborative coordination for multirobot systems","volume":"23","author":"Liu","year":"2024","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"4130","DOI":"10.1109\/TNNLS.2021.3123240","article-title":"Initialization-based k-winners-take-all neural network model using modified gradient descent","volume":"34","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1109\/TNN.2006.881046","article-title":"A simplified dual neural network for quadratic programming with its KWTA application","volume":"17","author":"Liu","year":"2006","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1016\/j.neunet.2009.03.020","article-title":"A novel neural dynamical approach to convex quadratic program and its efficient applications","volume":"22","author":"Xia","year":"2009","journal-title":"Neural Netw."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"108868","DOI":"10.1016\/j.automatica.2020.108868","article-title":"Analysis and design of a distributed k-winners-take-all model","volume":"115","author":"Zhang","year":"2020","journal-title":"Automatica"},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"119528","DOI":"10.1016\/j.ins.2023.119528","article-title":"Single-state distributed k-winners-take-all neural network model","volume":"647","author":"Zhang","year":"2023","journal-title":"Inf. Sci."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"5069","DOI":"10.1109\/TCYB.2022.3170236","article-title":"Distributed k-winners-take-all network: An optimization perspective","volume":"53","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Cybern."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"122938","DOI":"10.1016\/j.eswa.2023.122938","article-title":"Inter-robot management via neighboring robot sensing and measurement using a zeroing neural dynamics approach","volume":"244","author":"Liao","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"128384","DOI":"10.1016\/j.neucom.2024.128384","article-title":"A varying-parameter complementary neural network for multi-robot tracking and formation via model predictive control","volume":"609","author":"Li","year":"2024","journal-title":"Neurocomputing"},{"key":"ref_126","first-page":"137","article-title":"Energy-efficient scheduling with reliability guarantee in embedded real-time systems","volume":"18","author":"Xu","year":"2018","journal-title":"Sustain. Comput. Inform."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"104915","DOI":"10.1016\/j.jpdc.2024.104915","article-title":"Energy-efficient triple modular redundancy scheduling on heterogeneous multi-core real-time systems","volume":"191","author":"Xu","year":"2024","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"103137","DOI":"10.1016\/j.sysarc.2024.103173","article-title":"Energy-efficient scheduling for parallel applications with reliability and time constraints on heterogeneous distributed systems","volume":"152","author":"Xu","year":"2024","journal-title":"J. Syst. Archit."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1587\/transinf.2023EDP7262","article-title":"A two-phase algorithm for reliable and energy-efficient heterogeneous embedded systems","volume":"E107.D","author":"Xu","year":"2024","journal-title":"IEICE Trans. Inf. Syst."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.jpdc.2019.01.006","article-title":"Minimizing energy consumption with reliability goal on heterogeneous embedded systems","volume":"127","author":"Xu","year":"2019","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"110667","DOI":"10.1016\/j.comnet.2024.110667","article-title":"Simultaneous update of sensing and control data using free-ride codes in vehicular networks: An age and energy perspective","volume":"252","author":"Xie","year":"2024","journal-title":"Computer Netw."},{"key":"ref_132","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, S., Wu, Y., and Deng, Q. (2021, January 22\u201324). Distributed connectivity maximization for networked mobile robots with collision avoidance. Proceedings of the 2021 33rd Chinese Control and Decision Conference (CCDC), Kunming, China.","DOI":"10.1109\/CCDC52312.2021.9601425"},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Zhang, Y. (2020, January 27\u201328). Near-optimal consensus of multi-dimensional double-integrator multi-agent systems. Proceedings of the 2020 3rd International Conference on Unmanned Systems (ICUS), Harbin, China.","DOI":"10.1109\/ICUS50048.2020.9274969"},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"4119","DOI":"10.1109\/TETCI.2024.3386692","article-title":"Privacy-preserving consensus of double-integrator multi-agent systems with input constraints","volume":"8","author":"Deng","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1109\/TNNLS.2017.2652478","article-title":"A collaborative neurodynamic approach to multiple-objective distributed optimization","volume":"29","author":"Yang","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"3149","DOI":"10.1109\/TCYB.2017.2760908","article-title":"A neurodynamic approach to distributed optimization with globally coupled constraints","volume":"48","author":"Le","year":"2018","journal-title":"IEEE Trans. Cybern."},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"10031","DOI":"10.1109\/TII.2024.3383508","article-title":"A neurodynamic approach for solving time-dependent nonlinear equation system: A distributed optimization perspective","volume":"20","author":"Li","year":"2024","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"3141","DOI":"10.1109\/TSMC.2022.3221937","article-title":"A collaborative neurodynamic approach to distributed global optimization","volume":"53","author":"Xia","year":"2023","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1109\/TCST.2017.2699167","article-title":"Distributed maneuvering of autonomous surface vehicles based on neurodynamic optimization and fuzzy approximation","volume":"26","author":"Peng","year":"2018","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"4366","DOI":"10.1109\/TAC.2023.3319132","article-title":"Low-computational-complexity zeroing neural network model for solving systems of dynamic nonlinear equations","volume":"69","author":"Zheng","year":"2024","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_141","doi-asserted-by":"crossref","unstructured":"Zhang, Y., and Li, S. (2020). Machine Behavior Design And Analysis: A Consensus Perspective, Springer.","DOI":"10.1007\/978-981-15-3231-3"},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1109\/TSMC.2018.2882558","article-title":"Consensus of high-order discrete-time multiagent systems with switching topology","volume":"51","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"4750","DOI":"10.1109\/TNSM.2024.3400283","article-title":"ContexLog: Non-parsing log anomaly detection with all information preservation and enhanced contextual representation","volume":"21","author":"Xiao","year":"2024","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_144","doi-asserted-by":"crossref","unstructured":"Zhang, P., and Zhang, Y. (2021, January 3\u20137). A BAS algorithm based neural network for intrusion detection. Proceedings of the 2021 11th International Conference on Intelligent Control and Information Processing (ICICIP), Dali, China.","DOI":"10.1109\/ICICIP53388.2021.9642170"},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1109\/LCOMM.2018.2789911","article-title":"Analytical expressions for the probability of false-alarm and decision threshold of Hadamard ratio detector in non-asymptotic scenarios","volume":"22","author":"Yang","year":"2018","journal-title":"IEEE Commu. Lett."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"6521","DOI":"10.1109\/JIOT.2023.3314764","article-title":"Secure and real-time traceable data sharing in cloud-assisted IoT","volume":"11","author":"Lu","year":"2024","journal-title":"IEEE Internet Things J."},{"key":"ref_147","first-page":"3023298","article-title":"Investigation of E-commerce security and data platform based on the era of big data of the internet of things","volume":"2022","author":"Dai","year":"2022","journal-title":"Mobile Inform. Syst."},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1007\/s44196-023-00277-8","article-title":"Structural analysis of the evolution mechanism of online public opinion and its development stages based on machine learning and social network analysis","volume":"16","author":"Liu","year":"2023","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"2802","DOI":"10.1109\/TCBB.2023.3283801","article-title":"A new binary biclustering algorithm based on weight adjacency difference matrix for analyzing gene expression data","volume":"20","author":"Chu","year":"2023","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"10775","DOI":"10.1007\/s00500-022-06992-2","article-title":"Decision support system for evaluating the role of music in network-based game for sustaining effectiveness","volume":"26","author":"Yu","year":"2022","journal-title":"Soft Comput."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/TG.2020.3035593","article-title":"Controlling melody structures in automatic game soundtrack compositions with adversarial learning guided Gaussian mixture models","volume":"13","author":"Xiang","year":"2021","journal-title":"IEEE Trans. Games"},{"key":"ref_152","first-page":"3047","article-title":"Real-Time Formation Planning for Multi-robot Cooperation: A Neural Informatics Perspective","volume":"52","author":"Wang","year":"2025","journal-title":"IEEE Trans. Ind. Electron."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/6\/936\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:50:47Z","timestamp":1760032247000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/6\/936"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,12]]},"references-count":152,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["sym17060936"],"URL":"https:\/\/doi.org\/10.3390\/sym17060936","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,12]]}}}