{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T06:45:03Z","timestamp":1759041903539,"version":"3.37.3"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T00:00:00Z","timestamp":1564704000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T00:00:00Z","timestamp":1564704000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1007\/s00521-019-04390-8","type":"journal-article","created":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T11:29:02Z","timestamp":1564745342000},"page":"9221-9240","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A novel application of kernel adaptive filtering algorithms for attenuation of noise interferences"],"prefix":"10.1007","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6219-4910","authenticated-orcid":false,"given":"Muhammad Asif Zahoor","family":"Raja","sequence":"first","affiliation":[]},{"given":"Naveed Ishtiaq","family":"Chaudhary","sequence":"additional","affiliation":[]},{"given":"Zaheer","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Ata","family":"Ur Rehman","sequence":"additional","affiliation":[]},{"given":"Muhammad Saeed","family":"Aslam","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,2]]},"reference":[{"key":"4390_CR1","first-page":"30","volume-title":"Handbook of acoustical measurements and noise control","author":"CM Harris","year":"1991","unstructured":"Harris CM (1991) Handbook of acoustical measurements and noise control. McGraw-Hill, New York, pp 30\u201345"},{"issue":"2","key":"4390_CR2","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1109\/TASSP.1979.1163209","volume":"27","author":"S Boll","year":"1979","unstructured":"Boll S (1979) Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans Acoust Speech Signal Process 27(2):113\u2013120","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"key":"4390_CR3","volume-title":"Acoustic echo and noise control: a practical approach","author":"E H\u00e4nsler","year":"2005","unstructured":"H\u00e4nsler E, Schmidt G (2005) Acoustic echo and noise control: a practical approach, vol 40. Wiley, New York"},{"key":"4390_CR4","volume-title":"Active noise control systems: algorithms and DSP implementations","author":"SM Kuo","year":"1995","unstructured":"Kuo SM, Morgan D (1995) Active noise control systems: algorithms and DSP implementations. Wiley, New York"},{"issue":"4","key":"4390_CR5","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1109\/79.248551","volume":"10","author":"SJ Elliott","year":"1993","unstructured":"Elliott SJ, Nelson PA (1993) Active noise control. IEEE Signal Process Mag 10(4):12\u201335","journal-title":"IEEE Signal Process Mag"},{"issue":"6","key":"4390_CR6","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1109\/5.763310","volume":"87","author":"SM Kuo","year":"1999","unstructured":"Kuo SM, Morgan DR (1999) Active noise control: a tutorial review. Proc IEEE 87(6):943\u2013973","journal-title":"Proc IEEE"},{"issue":"2","key":"4390_CR7","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.sigpro.2012.08.013","volume":"93","author":"NV George","year":"2013","unstructured":"George NV, Panda G (2013) Advances in active noise control: a survey, with emphasis on recent nonlinear techniques. Sig Process 93(2):363\u2013377","journal-title":"Sig Process"},{"issue":"4","key":"4390_CR8","doi-asserted-by":"publisher","first-page":"454","DOI":"10.1109\/89.771315","volume":"7","author":"SC Douglas","year":"1999","unstructured":"Douglas SC (1999) Fast implementations of the filtered-X LMS and LMS algorithms for multichannel active noise control. IEEE Trans Speech Audio Process 7(4):454\u2013465","journal-title":"IEEE Trans Speech Audio Process"},{"issue":"6","key":"4390_CR9","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1109\/89.482218","volume":"3","author":"E Bjarnason","year":"1995","unstructured":"Bjarnason E (1995) Analysis of the filtered-X LMS algorithm. IEEE Trans Speech Audio Process 3(6):504\u2013514","journal-title":"IEEE Trans Speech Audio Process"},{"issue":"2","key":"4390_CR10","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1109\/TSA.2005.855829","volume":"14","author":"MT Akhtar","year":"2006","unstructured":"Akhtar MT, Abe M, Kawamata M (2006) A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems. IEEE Trans Audio Speech Lang Process 14(2):720\u2013726","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"4390_CR11","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/j.sigpro.2014.04.012","volume":"107","author":"MS Aslam","year":"2015","unstructured":"Aslam MS, Raja MAZ (2015) A new adaptive strategy to improve online secondary path modeling in active noise control systems using fractional signal processing approach. Signal Process 107:433\u2013443","journal-title":"Signal Process"},{"issue":"14","key":"4390_CR12","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1049\/el.2014.1275","volume":"50","author":"SM Shah","year":"2014","unstructured":"Shah SM, Samar R, Raja MAZ, Chambers JA (2014) Fractional normalised filtered-error least mean squares algorithm for application in active noise control systems. Electron Lett 50(14):973\u2013975","journal-title":"Electron Lett"},{"issue":"3","key":"4390_CR13","doi-asserted-by":"publisher","first-page":"1363","DOI":"10.1007\/s11071-016-2765-6","volume":"85","author":"SM Shah","year":"2016","unstructured":"Shah SM, Samar R, Khan NM, Raja MAZ (2016) Fractional-order adaptive signal processing strategies for active noise control systems. Nonlinear Dyn 85(3):1363\u20131376","journal-title":"Nonlinear Dyn"},{"key":"4390_CR14","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.ymssp.2018.10.031","volume":"120","author":"S Zhang","year":"2019","unstructured":"Zhang S, Wang YS, Guo H, Yang C, Wang XL, Liu NN (2019) A normalized frequency-domain block filtered-x LMS algorithm for active vehicle interior noise control. Mech Syst Signal Process 120:150\u2013165","journal-title":"Mech Syst Signal Process"},{"issue":"3\u20134","key":"4390_CR15","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1504\/IJVNV.2017.089525","volume":"13","author":"T Feng","year":"2017","unstructured":"Feng T, Sun G, Li M, Lim TC (2017) Channel self-adjusting filtered-x LMS algorithm for active control of vehicle road noise. Int J Veh Noise Vib 13(3\u20134):267\u2013281","journal-title":"Int J Veh Noise Vib"},{"issue":"9","key":"4390_CR16","doi-asserted-by":"publisher","first-page":"2315","DOI":"10.1109\/TIM.2009.2036410","volume":"59","author":"CY Chang","year":"2010","unstructured":"Chang CY, Chen DR (2010) Active noise cancellation without secondary path identification by using an adaptive genetic algorithm. IEEE Trans Instrum Meas 59(9):2315\u20132327","journal-title":"IEEE Trans Instrum Meas"},{"key":"4390_CR17","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.asoc.2016.01.011","volume":"41","author":"NK Rout","year":"2016","unstructured":"Rout NK, Das DP, Panda G (2016) Particle swarm optimization based nonlinear active noise control under saturation nonlinearity. Appl Soft Comput 41:275\u2013289","journal-title":"Appl Soft Comput"},{"issue":"12","key":"4390_CR18","doi-asserted-by":"publisher","first-page":"3378","DOI":"10.1109\/TIM.2012.2205492","volume":"61","author":"NV George","year":"2012","unstructured":"George NV, Panda G (2012) A particle-swarm-optimization-based decentralized nonlinear active noise control system. IEEE Trans Instrum Meas 61(12):3378\u20133386","journal-title":"IEEE Trans Instrum Meas"},{"key":"4390_CR19","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1016\/j.asoc.2018.08.027","volume":"73","author":"WU Khan","year":"2018","unstructured":"Khan WU, Ye Z, Chaudhary NI, Raja MAZ (2018) Backtracking search integrated with sequential quadratic programming for nonlinear active noise control systems. Appl Soft Comput 73:666\u2013683","journal-title":"Appl Soft Comput"},{"issue":"2","key":"4390_CR20","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1631\/FITEE.1601028","volume":"19","author":"MAZ Raja","year":"2018","unstructured":"Raja MAZ, Aslam MS, Chaudhary NI, Khan WU (2018) Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path. Front Inf Technol Electron Eng 19(2):246\u2013259","journal-title":"Front Inf Technol Electron Eng"},{"key":"4390_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3214-2","author":"MAZ Raja","year":"2017","unstructured":"Raja MAZ, Aslam MS, Chaudhary NI, Nawaz M, Shah SM (2017) Design of hybrid nature-inspired heuristics with application to active noise control systems.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-017-3214-2","journal-title":"Neural Comput Appl"},{"issue":"1","key":"4390_CR22","first-page":"89","volume":"12","author":"Z Momani","year":"2018","unstructured":"Momani Z, Al Shridah M, Arqub OA, Al-Momani M, Momani S (2018) Modeling and analyzing neural networks using reproducing kernel Hilbert space algorithm. Appl Math 12(1):89\u201399","journal-title":"Appl Math"},{"issue":"5","key":"4390_CR23","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1007\/s00521-016-2484-4","volume":"29","author":"OA Arqub","year":"2018","unstructured":"Arqub OA, Maayah B (2018) Solutions of Bagley-Torvik and Painlev\u00e9 equations of fractional order using iterative reproducing kernel algorithm with error estimates. Neural Comput Appl 29(5):1465\u20131479","journal-title":"Neural Comput Appl"},{"issue":"7","key":"4390_CR24","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1007\/s00521-015-2110-x","volume":"28","author":"OA Arqub","year":"2017","unstructured":"Arqub OA (2017) Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm\u2013Volterra integrodifferential equations. Neural Comput Appl 28(7):1591\u20131610","journal-title":"Neural Comput Appl"},{"issue":"8","key":"4390_CR25","doi-asserted-by":"publisher","first-page":"2595","DOI":"10.1007\/s00521-017-2845-7","volume":"30","author":"OA Arqub","year":"2018","unstructured":"Arqub OA, Rashaideh H (2018) The RKHS method for numerical treatment for integrodifferential algebraic systems of temporal two-point BVPs.\u00a0Neural Comput Appl 30(8):2595\u20132606","journal-title":"Neural Comput Appl"},{"key":"4390_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3184-4","author":"M Emamjome","year":"2017","unstructured":"Emamjome M, Azarnavid B, Ghehsareh HR (2017) A reproducing kernel Hilbert space pseudospectral method for numerical investigation of a two-dimensional capillary formation model in tumor angiogenesis problem.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-017-3184-4","journal-title":"Neural Comput Appl"},{"issue":"2","key":"4390_CR27","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1109\/TSP.2007.907881","volume":"56","author":"W Liu","year":"2008","unstructured":"Liu W, Pokharel PP, Principe JC (2008) The kernel least-mean-square algorithm. IEEE Trans Signal Process 56(2):543\u2013554","journal-title":"IEEE Trans Signal Process"},{"issue":"11","key":"4390_CR28","doi-asserted-by":"publisher","first-page":"2624","DOI":"10.1016\/j.sigpro.2012.04.007","volume":"92","author":"B Chen","year":"2012","unstructured":"Chen B, Zhao S, Zhu P, Pr\u00edncipe JC (2012) Mean square convergence analysis for kernel least mean square algorithm. Signal Process 92(11):2624\u20132632","journal-title":"Signal Process"},{"key":"4390_CR29","volume-title":"Kernel adaptive filtering: a comprehensive introduction","author":"W Liu","year":"2011","unstructured":"Liu W, Principe JC, Haykin S (2011) Kernel adaptive filtering: a comprehensive introduction, vol 57. Wiley, New York"},{"issue":"2","key":"4390_CR30","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1109\/TNNLS.2013.2272594","volume":"25","author":"FA Tobar","year":"2014","unstructured":"Tobar FA, Kung SY, Mandic DP (2014) Multikernel least mean square algorithm. IEEE Trans Neural Netw Learn Syst 25(2):265\u2013277","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"9","key":"4390_CR31","doi-asserted-by":"publisher","first-page":"1867","DOI":"10.1109\/TASL.2013.2260742","volume":"21","author":"JM Gil-Cacho","year":"2013","unstructured":"Gil-Cacho JM, Signoretto M, van Waterschoot T, Moonen M, Jensen SH (2013) Nonlinear acoustic echo cancellation based on a sliding-window leaky kernel affine projection algorithm. IEEE Trans Audio Speech Lang Process 21(9):1867\u20131878","journal-title":"IEEE Trans Audio Speech Lang Process"},{"issue":"4","key":"4390_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JPHOT.2016.2585105","volume":"8","author":"R Mitra","year":"2016","unstructured":"Mitra R, Bhatia V (2016) Adaptive sparse dictionary-based kernel minimum symbol error rate post-distortion for nonlinear LEDs in visible light communications. IEEE Photonics J 8(4):1\u201313","journal-title":"IEEE Photonics J"},{"issue":"2","key":"4390_CR33","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1007\/s11071-017-3707-7","volume":"90","author":"L Lu","year":"2017","unstructured":"Lu L, Zhao H, Chen B (2017) Time series prediction using kernel adaptive filter with least mean absolute third loss function. Nonlinear Dyn 90(2):999\u20131013","journal-title":"Nonlinear Dyn"},{"issue":"12\u201313","key":"4390_CR34","doi-asserted-by":"publisher","first-page":"2062","DOI":"10.1016\/j.neucom.2010.12.026","volume":"74","author":"HS Yazdi","year":"2011","unstructured":"Yazdi HS, Pakdaman M, Modaghegh H (2011) Unsupervised kernel least mean square algorithm for solving ordinary differential equations. Neurocomputing 74(12\u201313):2062\u20132071","journal-title":"Neurocomputing"},{"key":"4390_CR35","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/467276","author":"NI Chaudhary","year":"2013","unstructured":"Chaudhary NI, Raja MAZ, Khan JA, Aslam MS (2013) Identification of input nonlinear control autoregressive systems using fractional signal processing approach.\u00a0Sci World J. \n                    https:\/\/doi.org\/10.1155\/2013\/467276","journal-title":"Sci World J"},{"issue":"2","key":"4390_CR36","doi-asserted-by":"publisher","first-page":"1385","DOI":"10.1007\/s11071-014-1748-8","volume":"79","author":"NI Chaudhary","year":"2015","unstructured":"Chaudhary NI, Raja MAZ (2015) Identification of Hammerstein nonlinear ARMAX systems using nonlinear adaptive algorithms. Nonlinear Dyn 79(2):1385\u20131397","journal-title":"Nonlinear Dyn"},{"key":"4390_CR37","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.sigpro.2015.04.015","volume":"116","author":"NI Chaudhary","year":"2015","unstructured":"Chaudhary NI, Raja MAZ (2015) Design of fractional adaptive strategy for input nonlinear Box\u2013Jenkins systems. Signal Process 116:141\u2013151","journal-title":"Signal Process"},{"key":"4390_CR38","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3629-4","author":"S Zhang","year":"2018","unstructured":"Zhang S, Tan W, Wang Q, Wang N (2018) A new method of online extreme learning machine based on hybrid kernel function.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-018-3629-4","journal-title":"Neural Comput Appl"},{"key":"4390_CR39","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3342-3","author":"M Zhao","year":"2018","unstructured":"Zhao M, Tian Z, Chow TW (2018) Fault diagnosis on wireless sensor network using the neighborhood kernel density estimation.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-018-3342-3","journal-title":"Neural Comput Appl"},{"issue":"8","key":"4390_CR40","doi-asserted-by":"publisher","first-page":"2355","DOI":"10.1007\/s00521-016-2818-2","volume":"30","author":"H Faris","year":"2018","unstructured":"Faris H, Hassonah MA, Ala\u2019M AZ, Mirjalili S, Aljarah I (2018) A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture. Neural Comput Appl 30(8):2355\u20132369","journal-title":"Neural Comput Appl"},{"issue":"11","key":"4390_CR41","doi-asserted-by":"publisher","first-page":"3429","DOI":"10.1007\/s00521-016-2206-y","volume":"28","author":"X Xie","year":"2017","unstructured":"Xie X, Li B, Chai X (2017) A manifold framework of multiple-kernel learning for hyperspectral image classification. Neural Comput Appl 28(11):3429\u20133439","journal-title":"Neural Comput Appl"},{"key":"4390_CR42","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3931-1","author":"AH Sodhro","year":"2019","unstructured":"Sodhro AH, Malokani AS, Sodhro GH, Muzammal M, Zongwei L (2019) An adaptive QoS computation for medical data processing in intelligent healthcare applications.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-018-3931-1","journal-title":"Neural Comput Appl"},{"key":"4390_CR43","doi-asserted-by":"publisher","first-page":"42384","DOI":"10.1109\/ACCESS.2018.2859205","volume":"6","author":"AH Sodhro","year":"2018","unstructured":"Sodhro AH, Pirbhulal S, Qaraqe M, Lohano S, Sodhro GH, Junejo NUR, Luo Z (2018) Power control algorithms for media transmission in remote healthcare systems. IEEE Access 6:42384\u201342393","journal-title":"IEEE Access"},{"key":"4390_CR44","first-page":"589","volume-title":"Handbook of large-scale distributed computing in smart healthcare. Scalable computing and communications","author":"AH Sodhro","year":"2017","unstructured":"Sodhro AH, Shaikh FK, Pirbhulal S, Lodro MM, Shah MA (2017) Medical-QoS based telemedicine service selection using analytic hierarchy process. In:\u00a0Khan S, Zomaya A, Abbas A (eds) Handbook of large-scale distributed computing in smart healthcare. Scalable computing and communications. Springer, Cham, pp 589\u2013609"},{"key":"4390_CR45","doi-asserted-by":"crossref","unstructured":"Magsi H, Sodhro AH, Chachar FA, Abro SAK, Sodhro GH, Pirbhulal S (2018) Evolution of 5G in Internet of medical things. In: 2018 international conference on computing, mathematics and engineering technologies (iCoMET). IEEE, pp 1\u20137","DOI":"10.1109\/ICOMET.2018.8346428"},{"key":"4390_CR46","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2018.2881611","author":"AH Sodhro","year":"2018","unstructured":"Sodhro AH, Pirbhulal S, Sodhro GH, Gurtov A, Muzammal M, Luo Z (2018) A joint transmission power control and duty-cycle approach for smart healthcare system.\u00a0IEEE Sens J. \n                    https:\/\/doi.org\/10.1109\/JSEN.2018.2881611","journal-title":"IEEE Sens J"},{"key":"4390_CR47","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4020-6042-7","volume-title":"Advances in fractional calculus","author":"JATMJ Sabatier","year":"2007","unstructured":"Sabatier JATMJ, Agrawal OP, Machado JT (2007) Advances in fractional calculus, vol 4. Springer, Dordrecht"},{"issue":"3","key":"4390_CR48","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1016\/j.cnsns.2010.05.027","volume":"16","author":"JT Machado","year":"2011","unstructured":"Machado JT, Kiryakova V, Mainardi F (2011) Recent history of fractional calculus. Commun Nonlinear Sci Numer Simul 16(3):1140\u20131153","journal-title":"Commun Nonlinear Sci Numer Simul"},{"key":"4390_CR49","doi-asserted-by":"publisher","DOI":"10.1142\/8180","volume-title":"Fractional calculus: models and numerical methods","author":"D Baleanu","year":"2012","unstructured":"Baleanu D (2012) Fractional calculus: models and numerical methods, vol 3. World Scientific, Singapore"},{"volume-title":"Fractional dynamics and control","year":"2011","key":"4390_CR50","unstructured":"Baleanu D, Machado JAT, Luo AC (eds) (2011) Fractional dynamics and control. Springer, Berlin"},{"issue":"5","key":"4390_CR51","doi-asserted-by":"publisher","first-page":"D4016005","DOI":"10.1061\/(ASCE)EM.1943-7889.0001091","volume":"143","author":"A Atangana","year":"2017","unstructured":"Atangana A, Baleanu D (2017) Caputo-Fabrizio derivative applied to groundwater flow within confined aquifer. J Eng Mech 143(5):D4016005","journal-title":"J Eng Mech"},{"key":"4390_CR52","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.apm.2018.09.028","volume":"66","author":"NI Chaudhary","year":"2019","unstructured":"Chaudhary NI, Zubair S, Raja MAZ, Dedovic N (2019) Normalized fractional adaptive methods for nonlinear control autoregressive systems. Appl Math Model 66:457\u2013471","journal-title":"Appl Math Model"},{"issue":"6","key":"4390_CR53","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s00521-016-2548-5","volume":"29","author":"NI Chaudhary","year":"2018","unstructured":"Chaudhary NI, Raja MAZ, Aslam MS, Ahmed N (2018) Novel generalization of Volterra LMS algorithm to fractional order with application to system identification. Neural Comput Appl 29(6):41\u201358","journal-title":"Neural Comput Appl"},{"key":"4390_CR54","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3362-z","author":"NI Chaudhary","year":"2018","unstructured":"Chaudhary NI, Manzar MA, Raja MAZ (2018) Fractional Volterra LMS algorithm with application to Hammerstein control autoregressive model identification.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-018-3362-z","journal-title":"Neural Comput Appl"},{"issue":"3","key":"4390_CR55","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1007\/s11760-012-0316-2","volume":"6","author":"MS Couceiro","year":"2012","unstructured":"Couceiro MS, Rocha RP, Ferreira NF, Machado JT (2012) Introducing the fractional-order Darwinian PSO. SIViP 6(3):343\u2013350","journal-title":"SIViP"},{"key":"4390_CR56","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.matcom.2016.08.002","volume":"132","author":"MAZ Raja","year":"2017","unstructured":"Raja MAZ, Samar R, Manzar MA, Shah SM (2017) Design of unsupervised fractional neural network model optimized with interior point algorithm for solving Bagley\u2013Torvik equation. Math Comput Simul 132:139\u2013158","journal-title":"Math Comput Simul"},{"issue":"1","key":"4390_CR57","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s00521-017-2991-y","volume":"31","author":"S Lodhi","year":"2019","unstructured":"Lodhi S, Manzar MA, Raja MAZ (2019) Fractional neural network models for nonlinear Riccati systems.\u00a0Neural Comput Appl 31(1):359\u2013378","journal-title":"Neural Comput Appl"},{"issue":"12","key":"4390_CR58","doi-asserted-by":"publisher","first-page":"1625","DOI":"10.1016\/j.robot.2012.09.021","volume":"60","author":"MS Couceiro","year":"2012","unstructured":"Couceiro MS, Machado JT, Rocha RP, Ferreira NM (2012) A fuzzified systematic adjustment of the robotic Darwinian PSO. Robot Autonom Syst 60(12):1625\u20131639","journal-title":"Robot Autonom Syst"},{"key":"4390_CR59","doi-asserted-by":"crossref","unstructured":"Wang YY, Zhang H, Qiu CH, Xia SR (2018) A novel feature selection method based on extreme learning machine and fractional-order darwinian PSO.\u00a0Comput Intell Neurosci,\u00a02018","DOI":"10.1155\/2018\/5078268"},{"key":"4390_CR60","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3318-8","author":"S Akbar","year":"2018","unstructured":"Akbar S, Zaman F, Asif M, Rehman AU, Raja MAZ (2018) Novel application of FO-DPSO for 2-D parameter estimation of electromagnetic plane waves.\u00a0Neural Comput Appl. \n                    https:\/\/doi.org\/10.1007\/s00521-017-3318-8","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04390-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04390-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04390-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T09:18:39Z","timestamp":1596273519000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04390-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,2]]},"references-count":60,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["4390"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04390-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,8,2]]},"assertion":[{"value":"15 November 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 August 2019","order":3,"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":"All authors declared that there are no potential conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"All authors declared that there is no research involving human and\/or animal.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights statements"}},{"value":"All authors declared that there is no material that required informed consent.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}