{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T15:34:00Z","timestamp":1759937640736,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T00:00:00Z","timestamp":1578614400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T00:00:00Z","timestamp":1578614400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61873002","61703004"],"award-info":[{"award-number":["61873002","61703004"]}],"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":["61503002","61673339"],"award-info":[{"award-number":["61503002","61673339"]}],"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":["61573201"],"award-info":[{"award-number":["61573201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s11063-019-10175-w","type":"journal-article","created":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T12:09:15Z","timestamp":1578658155000},"page":"1939-1955","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["$$H_{\\infty }$$ Filtering for Markov Jump Neural Networks Subject to Hidden-Markov Mode Observation and Packet Dropouts via an Improved Activation Function Dividing Method"],"prefix":"10.1007","volume":"51","author":[{"given":"Feng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianrong","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xia","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7024-6573","authenticated-orcid":false,"given":"Hao","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,10]]},"reference":[{"issue":"7","key":"10175_CR1","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1109\/81.855465","volume":"47","author":"S Arik","year":"2000","unstructured":"Arik S (2000) Stability analysis of delayed neural networks. IEEE Trans Circuits Syst I Fund Theory Appl 47(7):1089\u20131092","journal-title":"IEEE Trans Circuits Syst I Fund Theory Appl"},{"key":"10175_CR2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2909748","author":"J Cheng","year":"2019","unstructured":"Cheng J, Park J, Cao J, Qi W (2019) Hidden Markov model-based nonfragile state estimation of switched neural network with probabilistic quantized outputs. IEEE Trans Cybern. https:\/\/doi.org\/10.1109\/TCYB.2019.2909748","journal-title":"IEEE Trans Cybern"},{"issue":"4","key":"10175_CR3","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.physleta.2006.01.061","volume":"354","author":"Z Wang","year":"2006","unstructured":"Wang Z, Liu Y, Fraser K, Liu X (2006) Stochastic stability of uncertain hopfield neural networks with discrete and distributed delays. Phys Lett A 354(4):288\u2013297","journal-title":"Phys Lett A"},{"issue":"5","key":"10175_CR4","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1080\/03081079.2013.780052","volume":"42","author":"CK Ahn","year":"2013","unstructured":"Ahn CK (2013) State estimation for T\u2013S fuzzy hopfield neural networks via strict output passivation of the error system. Int J General Syst 42(5):503\u2013518","journal-title":"Int J General Syst"},{"issue":"14","key":"10175_CR5","doi-asserted-by":"crossref","first-page":"6312","DOI":"10.1016\/j.jfranklin.2017.07.040","volume":"354","author":"R Manivannan","year":"2017","unstructured":"Manivannan R, Samidurai R, Zhu Q (2017) Further improved results on stability and dissipativity analysis of static impulsive neural networks with interval time-varying delays. J Frankl Inst 354(14):6312\u20136340","journal-title":"J Frankl Inst"},{"issue":"2","key":"10175_CR6","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1109\/TNNLS.2011.2179312","volume":"23","author":"J Lu","year":"2012","unstructured":"Lu J, Kurths J, Cao J, Mahdavi N, Huang C (2012) Synchronization control for nonlinear stochastic dynamical networks: pinning impulsive strategy. IEEE Trans Neural Netw Learn Syst 23(2):285\u2013292","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"5","key":"10175_CR7","doi-asserted-by":"crossref","first-page":"3486","DOI":"10.1137\/120897341","volume":"51","author":"X Yang","year":"2013","unstructured":"Yang X, Cao J, Yang Z (2013) Synchronization of coupled reaction\u2013diffusion neural networks with time-varying delays via pinning-impulsive controller. SIAM J Control Optim 51(5):3486\u20133510","journal-title":"SIAM J Control Optim"},{"key":"10175_CR8","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.inffus.2017.03.003","volume":"38","author":"J Hu","year":"2017","unstructured":"Hu J, Wang Z, Alsaadi FE, Hayat T (2017) Event-based filtering for time-varying nonlinear systems subject to multiple missing measurements with uncertain missing probabilities. Inform Fusion 38:74\u201383","journal-title":"Inform Fusion"},{"key":"10175_CR9","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-28847-5","volume-title":"Analysis and design of Markov jump systems with complex transition probabilities","author":"L Zhang","year":"2016","unstructured":"Zhang L, Yang T, Shi P, Zhu Y (2016) Analysis and design of Markov jump systems with complex transition probabilities. Springer, Berlin"},{"issue":"1","key":"10175_CR10","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/TFUZZ.2019.2939965","volume":"28","author":"H Shen","year":"2020","unstructured":"Shen H, Men Y, Cao J, Park J (2020) $${\\cal{H}}_{\\infty }$$ filtering for fuzzy jumping genetic regulatory networks with round-robin protocol: a hidden-Markov-model-based approach. IEEE Trans Fuzzy Syst 28(1):112\u2013121","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"9","key":"10175_CR11","doi-asserted-by":"crossref","first-page":"2951","DOI":"10.1109\/TCSI.2018.2797257","volume":"65","author":"W Qi","year":"2018","unstructured":"Qi W, Zong G, Karimi H (2018) Observer-based adaptive SMC for nonlinear uncertain singular semi-Markov jump systems with applications to DC motor. IEEE Trans Circuits Syst I Reg Papers 65(9):2951\u20132960","journal-title":"IEEE Trans Circuits Syst I Reg Papers"},{"key":"10175_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfranklin.2019.06.021","author":"J Cheng","year":"2019","unstructured":"Cheng J, Zhang D, Qi W, Cao J, Shi K (2019) Finite-time stabilization of T\u2013S fuzzy semi-Markov switching systems: a coupling memory sampled-data control approach. J Frankl Inst. https:\/\/doi.org\/10.1016\/j.jfranklin.2019.06.021","journal-title":"J Frankl Inst"},{"key":"10175_CR13","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2019.2921264","author":"H Shen","year":"2019","unstructured":"Shen H, Chen M, Wu Z, Cao J, Park J (2019) Reliable event-triggered asynchronous passive control for semi-Markov jump fuzzy systems and its application. IEEE Trans Fuzzy Syst. https:\/\/doi.org\/10.1109\/TFUZZ.2019.2921264","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"17","key":"10175_CR14","doi-asserted-by":"crossref","first-page":"5992","DOI":"10.1002\/rnc.4703","volume":"29","author":"J Cheng","year":"2019","unstructured":"Cheng J, Park J, Zhao X, Cao J, Qi W (2019) Static output feedback control of switched systems with quantization: a nonhomogeneous sojourn probability approach. Int J Robust Nonlinear Control 29(17):5992\u20136005","journal-title":"Int J Robust Nonlinear Control"},{"key":"10175_CR15","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.neucom.2017.11.065","volume":"281","author":"L Su","year":"2017","unstructured":"Su L, Ye D (2017) Mixed $$H_{\\infty }$$ and passive event-triggered reliable control for T\u2013S fuzzy Markov jump systems. Neurocomputing 281:96\u2013105","journal-title":"Neurocomputing"},{"issue":"1","key":"10175_CR16","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.jfranklin.2016.08.031","volume":"354","author":"AN Vargas","year":"2016","unstructured":"Vargas AN, Pujol G, Acho L (2016) Stability of Markov jump systems with quadratic terms and its application to RLC circuits. J Frankl Inst 354(1):332\u2013344","journal-title":"J Frankl Inst"},{"key":"10175_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2901867","author":"H Shen","year":"2019","unstructured":"Shen H, Huang Z, Cao J, Park J (2019) Exponential $${\\cal{H}}_{\\infty }$$ filtering for continuous-time switched neural networks under persistent dwell-time switching regularity. IEEE Trans Cybern. https:\/\/doi.org\/10.1109\/TCYB.2019.2901867","journal-title":"IEEE Trans Cybern"},{"issue":"8","key":"10175_CR18","doi-asserted-by":"crossref","first-page":"2709","DOI":"10.1109\/TAC.2017.2774006","volume":"63","author":"H Shen","year":"2018","unstructured":"Shen H, Li F, Xu S, Sreeram V (2018) Slow state variables feedback stabilization for semi-Markov jump systems with singular perturbations. IEEE Trans Autom Control 63(8):2709\u20132714","journal-title":"IEEE Trans Autom Control"},{"key":"10175_CR19","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2931533","author":"H Shen","year":"2019","unstructured":"Shen H, Jiao S, Huang T, Cao J (2019) An improved result on sampled-data synchronization of Markov jump delayed neural networks. IEEE Trans Syst Man Cybern Syst. https:\/\/doi.org\/10.1109\/TSMC.2019.2931533","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"10175_CR20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2909747","author":"H Shen","year":"2019","unstructured":"Shen H, Huo S, Yan H, Park J, Sreeram V (2019) Distributed dissipative state estimation for Markov jump genetic regulatory networks subject to round-robin scheduling. Neural Netw IEEE Trans Learn Syst. https:\/\/doi.org\/10.1109\/TNNLS.2019.2909747","journal-title":"Neural Netw IEEE Trans Learn Syst"},{"key":"10175_CR21","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.isatra.2016.11.004","volume":"66","author":"Q Li","year":"2017","unstructured":"Li Q, Zhu Q, Zhong S, Zhong F (2017) Extended dissipative state estimation for uncertain discrete-time markov jump neural networks with mixed time delays. ISA Trans 66:200\u2013208","journal-title":"ISA Trans"},{"issue":"4","key":"10175_CR22","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1109\/TNNLS.2015.2425962","volume":"27","author":"P Shi","year":"2016","unstructured":"Shi P, Zhang Y, Chadli M, Agarwal RK (2016) Mixed H-infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays. IEEE Trans Neural Netw Learn Syst 27(4):903\u2013909","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10175_CR23","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1007\/s13042-017-0651-2","volume":"9","author":"Y Li","year":"2018","unstructured":"Li Y, Deng F, Li G, Jiao L (2018) Robust $$H_{\\infty }$$ filtering for uncertain discrete-time stochastic neural networks with Markovian jump and mixed time-delays. Int J Mach Learn Cyber 9:1377\u20131386","journal-title":"Int J Mach Learn Cyber"},{"key":"10175_CR24","first-page":"467","volume":"271","author":"F Li","year":"2015","unstructured":"Li F, Shen H, Chen M, Kong Q (2015) Non-fragile finite-time $$l_{2}$$-$$l_{\\infty }$$ state estimation for discrete-time Markov jump neural networks with unreliable communication links. Appl Math Comput 271:467\u2013481","journal-title":"Appl Math Comput"},{"issue":"2","key":"10175_CR25","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1016\/j.jfranklin.2016.10.035","volume":"354","author":"J Ren","year":"2016","unstructured":"Ren J, Liu X, Zhu H, Zhong S, Shi K (2016) State estimation of neural networks with two Markovian jumping parameters and multiple time delays. J Frankl Inst 354(2):812\u2013833","journal-title":"J Frankl Inst"},{"issue":"17","key":"10175_CR26","doi-asserted-by":"crossref","first-page":"10155","DOI":"10.1016\/j.jfranklin.2018.01.021","volume":"356","author":"J Wang","year":"2019","unstructured":"Wang J, Xing M, Sun Y, Li J, Lu J (2019) Event-triggered dissipative state estimation for Markov jump neural networks with random uncertainties. J Frankl Inst 356(17):10155\u201310178","journal-title":"J Frankl Inst"},{"issue":"1","key":"10175_CR27","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.automatica.2013.09.041","volume":"50","author":"ZG Wu","year":"2014","unstructured":"Wu ZG, Shi P, Su H, Chu J (2014) Asynchronous $$l_{2}$$-$$l_{\\infty }$$ filtering for discrete-time stochastic Markov jump systems with randomly occurred sensor nonlinearities. Automatica 50(1):180\u2013186","journal-title":"Automatica"},{"issue":"12","key":"10175_CR28","doi-asserted-by":"crossref","first-page":"2840","DOI":"10.1109\/TCYB.2014.2387203","volume":"45","author":"L Zhang","year":"2015","unstructured":"Zhang L, Zhu Y, Shi P, Zhao Y (2015) Resilient asynchronous $$H_{\\infty }$$ filtering for Markov jump neural networks with unideal measurements and multiplicative noises. IEEE Trans Cybern 45(12):2840\u20132852","journal-title":"IEEE Trans Cybern"},{"issue":"17","key":"10175_CR29","doi-asserted-by":"crossref","first-page":"2175","DOI":"10.1049\/iet-cta.2016.0016","volume":"10","author":"J Wang","year":"2016","unstructured":"Wang J, Li F, Shen H, Sun Y (2016) On asynchronous $$l_{2}$$-$$l_{\\infty }$$ filtering for networked fuzzy systems with Markov jump parameters over a finite-time interval. IET Control Theory Appl 10(17):2175\u20132185","journal-title":"IET Control Theory Appl"},{"issue":"3","key":"10175_CR30","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1109\/TAC.2014.2366253","volume":"47","author":"OLdV Costa","year":"2015","unstructured":"Costa OLdV, Fragoso MD, Todorov MG (2015) A detector-based approach for the $$H_{2}$$ control of Markov jump linear systems with partial information. IEEE Trans Autom Control 47(3):1219\u20131234","journal-title":"IEEE Trans Autom Control"},{"issue":"4","key":"10175_CR31","doi-asserted-by":"crossref","first-page":"2020","DOI":"10.1109\/TAC.2016.2593742","volume":"62","author":"ZG Wu","year":"2017","unstructured":"Wu ZG, Shi P, Shu Z, Su H, Lu R (2017) Passivity-based asynchronous control for Markov jump systems. IEEE Trans Autom Control 62(4):2020\u20132025","journal-title":"IEEE Trans Autom Control"},{"issue":"8","key":"10175_CR32","doi-asserted-by":"crossref","first-page":"2426","DOI":"10.1109\/TCYB.2017.2739754","volume":"48","author":"ZG Wu","year":"2018","unstructured":"Wu ZG, Dong S, Su H, Li C (2018) Asynchronous dissipative control for fuzzy Markov jump systems. IEEE Trans Cybern 48(8):2426\u20132436","journal-title":"IEEE Trans Cybern"},{"key":"10175_CR33","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.automatica.2018.03.037","volume":"93","author":"J Song","year":"2018","unstructured":"Song J, Niu Y, Zou Y (2018) Asynchronous sliding mode control of Markovian jump systems with time-varying delays and partly accessible mode detection probabilities. Automatica 93:33\u201341","journal-title":"Automatica"},{"key":"10175_CR34","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ifacsc.2017.05.002","volume":"1","author":"AMD Oliveira","year":"2017","unstructured":"Oliveira AMD, Costa OLdV (2017) $$H_{\\infty }$$-filtering for Markov jump linear systems with partial information on the jump parameter. IFAC J Syst Control 1:13\u201323","journal-title":"IFAC J Syst Control"},{"key":"10175_CR35","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2837888","author":"F Li","year":"2018","unstructured":"Li F, Xu S, Zhang B (2018) Resilient asynchronous $$H_{\\infty }$$ control for discrete-time Markov jump singularly perturbed systems based on hidden Markov model. IEEE Trans Syst Man Cybern Syst. https:\/\/doi.org\/10.1109\/TSMC.2018.2837888","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"9","key":"10175_CR36","doi-asserted-by":"crossref","first-page":"1749","DOI":"10.1109\/TSMC.2018.2866906","volume":"49","author":"J Cheng","year":"2018","unstructured":"Cheng J, Ahn CK, Karimi HR, Cao J, Qi W (2018) An event-based asynchronous approach to Markov jump systems with hidden mode detections and missing measurements. IEEE Trans Syst Man Cybern Syst 49(9):1749\u20131758","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"10","key":"10175_CR37","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1109\/TFUZZ.2019.2892922","volume":"27","author":"F Li","year":"2019","unstructured":"Li F, Xu S, Shen H (2019) Fuzzy-model-based $$H_{\\infty }$$ control for Markov jump nonlinear slow sampling singularly perturbed systems with partial information. IEEE Trans Fuzzy Syst 27(10):1952\u20131962","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10175_CR38","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2847315","author":"J Song","year":"2018","unstructured":"Song J, Niu Y, Xu J (2018) An event-triggered approach to sliding mode control of Markovian jump lur\u2019e systems under hidden mode detections. IEEE Trans Syst Man Cybern Syst. https:\/\/doi.org\/10.1109\/TSMC.2018.2847315","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"15","key":"10175_CR39","doi-asserted-by":"crossref","first-page":"6747","DOI":"10.1016\/j.jfranklin.2017.08.028","volume":"354","author":"J Song","year":"2017","unstructured":"Song J, Niu Y, Zou Y (2017) Asynchronous output feedback control of time-varying Markovian jump systems within a finite-time interval. J Frankl Inst 354(15):6747\u20136765","journal-title":"J Frankl Inst"},{"key":"10175_CR40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cam.2019.03.046","volume":"360","author":"F Li","year":"2019","unstructured":"Li F, Song S, Zhao J, Xu S, Zhang Z (2019) Synchronization control for Markov jump neural networks subject to hmm observation and partially known detection probabilities. Appl Math Comput 360:1\u201313","journal-title":"Appl Math Comput"},{"issue":"7","key":"10175_CR41","doi-asserted-by":"crossref","first-page":"2504","DOI":"10.1109\/TCYB.2018.2824853","volume":"49","author":"J Tao","year":"2018","unstructured":"Tao J, Wu ZG, Su H, Wu Y, Zhang D (2018) Asynchronous and resilient filtering for Markovian jump neural networks subject to extended dissipativity. IEEE Trans Cybern 49(7):2504\u20132513","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"10175_CR42","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/TSMC.2017.2789180","volume":"49","author":"Y Shen","year":"2018","unstructured":"Shen Y, Wu ZG, Shi P, Su H, Huang T (2018) Asynchronous filtering for Markov jump neural networks with quantized outputs. IEEE Trans Syst Man Cybern Syst 49(2):433\u2013443","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"2","key":"10175_CR43","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1109\/TNNLS.2012.2224883","volume":"24","author":"OM Kwon","year":"2013","unstructured":"Kwon OM, Park MJ, Lee SM, Park JH, Cha EJ (2013) Stability for neural networks with time-varying delays via some new approaches. IEEE Trans Neural Netw Learn Syst 24(2):181\u2013193","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"10","key":"10175_CR44","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.1109\/TNNLS.2013.2296514","volume":"25","author":"TH Lee","year":"2014","unstructured":"Lee TH, Park MJ, Park JH, Kwon OM, Lee SM (2014) Extended dissipative analysis for neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst 25(10):1936\u20131941","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10175_CR45","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.ins.2016.08.064","volume":"372","author":"K Shi","year":"2016","unstructured":"Shi K, Liu X, Tang Y, Zhu H, Zhong S (2016) Some novel approaches on state estimation of delayed neural networks. Inf Sci 372:313\u2013331","journal-title":"Inf Sci"},{"key":"10175_CR46","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.automatica.2018.07.027","volume":"97","author":"J Hu","year":"2018","unstructured":"Hu J, Wang Z, Gao H (2018) Joint state and fault estimation for time-varying nonlinear systems with randomly occurring faults and sensor saturations. Automatica 97:150\u2013160","journal-title":"Automatica"},{"key":"10175_CR47","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.neucom.2018.07.086","volume":"346","author":"H Zhang","year":"2019","unstructured":"Zhang H, Hu J, Liu H, Yu X, Liu F (2019) Recursive state estimation for time-varying complex networks subject to missing measurements and stochastic inner coupling under random access protocol. Neurocomputing 346:48\u201357","journal-title":"Neurocomputing"},{"key":"10175_CR48","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.automatica.2017.03.020","volume":"80","author":"X Lin","year":"2017","unstructured":"Lin X, Chen C, Qian C (2017) Smooth output feedback stabilization of a class of planar switched nonlinear systems under arbitrary switchings. Automatica 80:314\u2013318","journal-title":"Automatica"},{"issue":"6","key":"10175_CR49","doi-asserted-by":"crossref","first-page":"2545","DOI":"10.1109\/TAC.2018.2867163","volume":"64","author":"S Ding","year":"2019","unstructured":"Ding S, Mei K, Li S (2019) A new second-order sliding mode and its application to nonlinear constrained systems. IEEE Trans Autom Control 64(6):2545\u20132552","journal-title":"IEEE Trans Autom Control"},{"issue":"1","key":"10175_CR50","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.automatica.2018.11.002","volume":"99","author":"H Du","year":"2019","unstructured":"Du H, Qian C, Li S, Chu Z (2019) Global sampled-data output feedback stabilization for a class of uncertain nonlinear systems. Automatica 99(1):403\u2013411","journal-title":"Automatica"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-019-10175-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-019-10175-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-019-10175-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,9]],"date-time":"2021-01-09T02:16:03Z","timestamp":1610158563000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-019-10175-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,10]]},"references-count":50,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["10175"],"URL":"https:\/\/doi.org\/10.1007\/s11063-019-10175-w","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2020,1,10]]},"assertion":[{"value":"10 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}