{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T08:25:58Z","timestamp":1768897558516,"version":"3.49.0"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2018,2,28]],"date-time":"2018-02-28T00:00:00Z","timestamp":1519776000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s11760-018-1250-8","type":"journal-article","created":{"date-parts":[[2018,2,28]],"date-time":"2018-02-28T12:15:42Z","timestamp":1519820142000},"page":"1079-1086","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Diffusion augmented complex adaptive IIR algorithm for training widely linear ARMA models"],"prefix":"10.1007","volume":"12","author":[{"given":"Azam","family":"Khalili","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,2,28]]},"reference":[{"issue":"5","key":"1250_CR1","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1149\/2.119406jes","volume":"31","author":"T Zhang","year":"2014","unstructured":"Zhang, T., Wang, B., Liu, S.: Widely linear rls constant modulus algorithm for complex-valued noncircular signals. J. Electron. 31(5), 416\u2013426 (2014)","journal-title":"J. Electron."},{"key":"1250_CR2","doi-asserted-by":"crossref","unstructured":"de Aquino, F. J. A., da Rocha, C.A.F., Resende, L.S.: Accelerating the convergence of the widely linear lms algorithm for channel equalization. In: Telecommunications Symposium: International 2006, pp. 734\u2013738 (2006)","DOI":"10.1109\/ITS.2006.4433369"},{"issue":"1","key":"1250_CR3","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/TIM.2011.2159409","volume":"61","author":"Y Xia","year":"2012","unstructured":"Xia, Y., Mandic, D.P.: Widely linear adaptive frequency estimation of unbalanced three-phase power systems. IEEE Trans. Instrum. Meas. 61(1), 74\u201383 (2012)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"8","key":"1250_CR4","doi-asserted-by":"publisher","first-page":"928","DOI":"10.1049\/iet-smt.2015.0018","volume":"9","author":"A Khalili","year":"2015","unstructured":"Khalili, A., Rastegarnia, A., Sanei, S.: Robust frequency estimation in three-phase power systems using correntropy-based adaptive filter. IET Sci. Meas. Technol. 9(8), 928\u2013935 (2015)","journal-title":"IET Sci. Meas. Technol."},{"key":"1250_CR5","doi-asserted-by":"crossref","unstructured":"Kuh, A., Manloloyo, C., Corpuz, R., Kowahl, N.: Wind prediction using complex augmented adaptive filters. In: 2010 International Conference on Green Circuits and Systems (ICGCS), pp. 46\u201350 (2010)","DOI":"10.1109\/ICGCS.2010.5543100"},{"issue":"1","key":"1250_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TNSRE.2013.2294903","volume":"22","author":"C Park","year":"2014","unstructured":"Park, C., Took, C.C., Mandic, D.P.: Augmented complex common spatial patterns for classification of noncircular eeg from motor imagery tasks. IEEE Trans. Neural Syst. Rehabil. Eng. 22(1), 1\u201310 (2014)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"1250_CR7","doi-asserted-by":"crossref","unstructured":"Li, L., Xia, Y., Jelfs, B., Cao, J., Mandic, D.P.: Modelling of brain consciousness based on collaborative adaptive filters. In: Neurocomputing, Seventh International Symposium on Neural Networks (ISNN 2010) Advances in Web Intelligence, vol.\u00a076, no.\u00a01, pp. 36\u201343 (2012)","DOI":"10.1016\/j.neucom.2011.05.038"},{"issue":"11","key":"1250_CR8","doi-asserted-by":"publisher","first-page":"5101","DOI":"10.1109\/TSP.2011.2162954","volume":"59","author":"T Adali","year":"2011","unstructured":"Adali, T., Schreier, P.J., Scharf, L.L.: Complex-valued signal processing: the proper way to deal with impropriety. IEEE Trans. Signal Process. 59(11), 5101\u20135125 (2011)","journal-title":"IEEE Trans. Signal Process."},{"key":"1250_CR9","series-title":"Widely Linear and Neural Models","doi-asserted-by":"publisher","DOI":"10.1002\/9780470742624","volume-title":"Complex Valued Nonlinear Adaptive Filters: Noncircularity","author":"D Mandic","year":"2009","unstructured":"Mandic, D., Goh, V.S.L.: Complex Valued Nonlinear Adaptive Filters: Noncircularity. Widely Linear and Neural Models. Wiley, New York (2009)"},{"key":"1250_CR10","unstructured":"Javidi, S., Pedzisz, M., Goh, S.L., Mandic, D.P.: The augmented complex least mean square algorithm. In: Proceedings of the 1st IARP Workshop on Cognitive Information Processing, pp. 54\u201357 (2008)"},{"key":"1250_CR11","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.sigpro.2015.10.034","volume":"121","author":"A Khalili","year":"2016","unstructured":"Khalili, A., Rastegarnia, A., Sanei, S.: Quantized augmented complex least-mean square algorithm: derivation and performance analysis. Signal Process. 121, 54\u201359 (2016)","journal-title":"Signal Process."},{"key":"1250_CR12","doi-asserted-by":"crossref","unstructured":"Xia, Y., Javidi, S., Mandic, D.P.: A regularised normalised augmented complex least mean square algorithm. In: Wireless Communication Systems (ISWCS): 7th International Symposium on 2010, pp. 355\u2013359 (2010)","DOI":"10.1109\/ISWCS.2010.5624272"},{"issue":"6","key":"1250_CR13","doi-asserted-by":"publisher","first-page":"1788","DOI":"10.1016\/j.sigpro.2009.11.026","volume":"90","author":"Y Xia","year":"2010","unstructured":"Xia, Y., Took, C.C., Mandic, D.P.: An augmented affine projection algorithm for the filtering of noncircular complex signals. Signal Process. 90(6), 1788\u20131799 (2010)","journal-title":"Signal Process."},{"key":"1250_CR14","doi-asserted-by":"crossref","unstructured":"Douglas, S.C.: Widely-linear recursive least-squares algorithm for adaptive beamforming. In: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2041\u20132044 (2009)","DOI":"10.1109\/ICASSP.2009.4960015"},{"issue":"11","key":"1250_CR15","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1109\/LSP.2011.2166259","volume":"18","author":"DH Dini","year":"2011","unstructured":"Dini, D.H., Mandic, D.P., Julier, S.J.: A widely linear complex unscented kalman filter. IEEE Signal Process. Lett. 18(11), 623\u2013626 (2011)","journal-title":"IEEE Signal Process. Lett."},{"issue":"10","key":"1250_CR16","doi-asserted-by":"publisher","first-page":"4111","DOI":"10.1109\/TSP.2009.2022353","volume":"57","author":"C Took","year":"2009","unstructured":"Took, C., Mandic, D.: Adaptive iir filtering of noncircular complex signals. IEEE Trans. Signal Process. 57(10), 4111\u20134118 (2009)","journal-title":"IEEE Trans. Signal Process."},{"issue":"2","key":"1250_CR17","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1109\/TIT.1984.1056883","volume":"30","author":"C Johnson","year":"1984","unstructured":"Johnson, C.: Adaptive iir filtering: current results and open issues. IEEE Trans. Inf. Theory 30(2), 237\u2013250 (1984)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"1250_CR18","volume-title":"Adaptive IIR Filtering in Signal Processing and Control","author":"PA Regalia","year":"1994","unstructured":"Regalia, P.A.: Adaptive IIR Filtering in Signal Processing and Control. Marcel Dekker, New York (1994)"},{"issue":"6","key":"1250_CR19","doi-asserted-by":"publisher","first-page":"910","DOI":"10.1109\/29.56052","volume":"38","author":"X Chen","year":"1990","unstructured":"Chen, X., Parks, T.W.: Design of IIR filters in the complex domain. IEEE Trans. Acoust. Speech Signal Process. 38(6), 910\u2013920 (1990)","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"issue":"9","key":"1250_CR20","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1109\/78.536690","volume":"44","author":"R Vuerinckx","year":"1996","unstructured":"Vuerinckx, R., Rolain, Y., Schoukens, J., Pintelon, R.: Design of stable IIR filters in the complex domain by automatic delay selection. IEEE Trans. Signal Process. 44(9), 2339\u20132344 (1996)","journal-title":"IEEE Trans. Signal Process."},{"issue":"7","key":"1250_CR21","doi-asserted-by":"publisher","first-page":"3061","DOI":"10.1109\/TSP.2008.919396","volume":"56","author":"J Navarro-Moreno","year":"2008","unstructured":"Navarro-Moreno, J.: Arma prediction of widely linear systems by using the innovations algorithm. IEEE Trans. Signal Process. 56(7), 3061\u20133068 (2008)","journal-title":"IEEE Trans. Signal Process."},{"issue":"2","key":"1250_CR22","first-page":"4","volume":"6","author":"J Shynk","year":"1989","unstructured":"Shynk, J.: Adaptive IIR filtering. IEEE Acoust. Speech Signal Process. ASSP Mag. 6(2), 4\u201321 (1989)","journal-title":"IEEE Acoust. Speech Signal Process. ASSP Mag."},{"issue":"8","key":"1250_CR23","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1109\/MCOM.2002.1024422","volume":"40","author":"I Akyildiz","year":"2002","unstructured":"Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40(8), 102\u2013114 (2002)","journal-title":"IEEE Commun. Mag."},{"issue":"3","key":"1250_CR24","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1007\/s11760-016-0986-2","volume":"11","author":"A Khalili","year":"2017","unstructured":"Khalili, A., Rastegarnia, A., Bazzi, W.M., Rahmati, R.G.: Incremental augmented complex adaptive IIR algorithm for training 449 widely linear ARMA model. Signal Image Video Process. 11(3), 493\u2013500 (2017)","journal-title":"Signal Image Video Process."},{"issue":"1","key":"1250_CR25","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1109\/TSP.2009.2025074","volume":"58","author":"L Li","year":"2010","unstructured":"Li, L., Chambers, J.A., Lopes, C.G., Sayed, A.H.: Distributed estimation over an adaptive incremental network based on the affine projection algorithm. IEEE Trans. Signal Process. 58(1), 151\u2013164 (2010)","journal-title":"IEEE Trans. Signal Process."},{"key":"1250_CR26","doi-asserted-by":"crossref","unstructured":"Ram, S., Nedic, A., Veeravalli, V.: Stochastic incremental gradient descent for estimation in sensor networks. In: Conference Record of the Forty-First Asilomar Conference on 2007 Signals, Systems and Computers: ACSSC 2007, pp. 582\u2013586 (2007)","DOI":"10.1109\/ACSSC.2007.4487280"},{"issue":"8","key":"1250_CR27","doi-asserted-by":"publisher","first-page":"2621","DOI":"10.1016\/j.sigpro.2010.02.019","volume":"90","author":"A Rastegarnia","year":"2010","unstructured":"Rastegarnia, A., Tinati, M.A., Khalili, A.: Performance analysis of quantized incremental LMS algorithm for distributed adaptive estimation. Signal Process. 90(8), 2621\u20132627 (2010)","journal-title":"Signal Process."},{"key":"1250_CR28","doi-asserted-by":"crossref","unstructured":"Lopes, C.G., Sayed, A.H.: Randomized incremental protocols over adaptive networks. In: Proceedings. IEEE International Conference on Acoustics Speech, Signal Processing (ICASSP), Dallas, pp. 3514\u20133517 (2010)","DOI":"10.1109\/ICASSP.2010.5495951"},{"key":"1250_CR29","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.sigpro.2013.07.001","volume":"94","author":"Y Liu","year":"2014","unstructured":"Liu, Y., Tang, W.K.: Enhanced incremental LMS with norm constraints for distributed in-network estimation. Signal Process. 94, 373\u2013385 (2014)","journal-title":"Signal Process."},{"issue":"3","key":"1250_CR30","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1109\/TSP.2009.2033729","volume":"58","author":"F Cattivelli","year":"2010","unstructured":"Cattivelli, F., Sayed, A.: Diffusion LMS strategies for distributed estimation. IEEE Trans. Signal Process. 58(3), 1035\u20131048 (2010)","journal-title":"IEEE Trans. Signal Process."},{"issue":"7","key":"1250_CR31","doi-asserted-by":"publisher","first-page":"3122","DOI":"10.1109\/TSP.2008.917383","volume":"56","author":"C Lopes","year":"2008","unstructured":"Lopes, C., Sayed, A.: Diffusion least-mean squares over adaptive networks: formulation and performance analysis. IEEE Trans. Signal Process. 56(7), 3122\u20133136 (2008)","journal-title":"IEEE Trans. Signal Process."},{"issue":"9","key":"1250_CR32","doi-asserted-by":"publisher","first-page":"4795","DOI":"10.1109\/TSP.2010.2051429","volume":"58","author":"N Takahashi","year":"2010","unstructured":"Takahashi, N., Yamada, I., Sayed, A.: Diffusion least-mean squares with adaptive combiners: formulation and performance analysis. IEEE Trans. Signal Process. 58(9), 4795\u20134810 (2010)","journal-title":"IEEE Trans. Signal Process."},{"key":"1250_CR33","doi-asserted-by":"crossref","unstructured":"Huang, S., Li, C.P: Distributed sparse total least-squares over networks. IEEE Trans. Signal Process. 99 (2015) (to appear)","DOI":"10.1109\/TSP.2015.2416671"},{"key":"1250_CR34","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.sigpro.2015.01.019","volume":"113","author":"J-W Lee","year":"2015","unstructured":"Lee, J.-W., Kim, S.-E., Song, W.-J.: Data-selective diffusion LMS for reducing communication overhead. Signal Process. 113, 211\u2013217 (2015)","journal-title":"Signal Process."},{"key":"1250_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.dsp.2014.09.004","volume":"36","author":"J Fernandez-Bes","year":"2015","unstructured":"Fernandez-Bes, J., Azpicueta-Ruiz, L.A., Arenas-Garca, J., Silva, M.T.: Distributed estimation in diffusion networks using affine least-squares combiners. Digit. Signal Process. 36, 1\u201314 (2015)","journal-title":"Digit. Signal Process."},{"issue":"1","key":"1250_CR36","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/TAC.2008.2009515","volume":"54","author":"A Nedic","year":"2009","unstructured":"Nedic, A., Ozdaglar, A.: Distributed subgradient methods for multi-agent optimization. IEEE Trans. Autom. Control 54(1), 48\u201361 (2009)","journal-title":"IEEE Trans. Autom. Control"},{"key":"1250_CR37","doi-asserted-by":"crossref","unstructured":"Olfati-Saber, R., Shamma, J.S.: Consensus filters for sensor networks and distributed sensor fusion. In: Proceedings of the 44th IEEE Conference on Decision and Control, pp. 6698\u20136703 (2005)","DOI":"10.1109\/CDC.2005.1583238"},{"issue":"15","key":"1250_CR38","doi-asserted-by":"publisher","first-page":"3924","DOI":"10.1109\/TSP.2014.2331615","volume":"62","author":"ZJ Towfic","year":"2014","unstructured":"Towfic, Z.J., Sayed, A.H.: Adaptive penalty-based distributed stochastic convex optimization. IEEE Trans. Signal Process. 62(15), 3924\u20133938 (2014)","journal-title":"IEEE Trans. Signal Process."},{"key":"1250_CR39","doi-asserted-by":"crossref","unstructured":"Lan, X., Ma, A.J., Yuen, P.C.: Multi-cue visual tracking using robust feature-level fusion based on joint sparse representation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1194\u20131201 (2014)","DOI":"10.1109\/CVPR.2014.156"},{"issue":"12","key":"1250_CR40","doi-asserted-by":"publisher","first-page":"5826","DOI":"10.1109\/TIP.2015.2481325","volume":"24","author":"X Lan","year":"2015","unstructured":"Lan, X., Ma, A.J., Yuen, P.C., Chellappa, R.: Joint sparse representation and robust feature-level fusion for multi-cue visual tracking. IEEE Trans. Image Process. 24(12), 5826\u20135841 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"1250_CR41","unstructured":"Lan, X., Zhang, S., Yuen, P.C.: Robust joint discriminative feature learning for visual tracking. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, ser. IJCAI\u201916. AAAI Press, pp. 3403\u20133410 (2016)"},{"key":"1250_CR42","doi-asserted-by":"crossref","unstructured":"Lan, X., Yuen, P.C., Chellappa, R.: Robust mil-based feature template learning for object tracking. In: AAAI (2017)","DOI":"10.1609\/aaai.v31i1.11220"},{"key":"1250_CR43","doi-asserted-by":"publisher","unstructured":"Lan, X., Zhang, S., Yuen, P.C., Chellappa, R.: Learning common and feature-specific patterns: a novel multiple-sparse-representation-based tracker. In: IEEE Transactions on Image Processing. https:\/\/doi.org\/10.1109\/TIP.2017.2777183 (to appear)","DOI":"10.1109\/TIP.2017.2777183"},{"issue":"7","key":"1250_CR44","doi-asserted-by":"publisher","first-page":"1750","DOI":"10.1109\/TSP.2014.2304432","volume":"62","author":"W Shi","year":"2014","unstructured":"Shi, W., Ling, Q., Yuan, K., Wu, G., Yin, W.: On the linear convergence of the admm in decentralized consensus optimization. IEEE Trans. Signal Process. 62(7), 1750\u20131761 (2014)","journal-title":"IEEE Trans. Signal Process."},{"issue":"11","key":"1250_CR45","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1109\/LSP.2011.2168390","volume":"18","author":"Y Xia","year":"2011","unstructured":"Xia, Y., Mandic, D.P., Sayed, A.H.: An adaptive diffusion augmented clms algorithm for distributed filtering of noncircular complex signals. IEEE Signal Process. Lett. 18(11), 659\u2013662 (2011)","journal-title":"IEEE Signal Process. Lett."},{"issue":"7","key":"1250_CR46","doi-asserted-by":"publisher","first-page":"3122","DOI":"10.1109\/TSP.2008.917383","volume":"56","author":"CG Lopes","year":"2008","unstructured":"Lopes, C.G., Sayed, A.H.: Diffusion least-mean squares over adaptive networks: formulation and performance analysis. IEEE Trans. Signal Process. 56(7), 3122\u20133136 (2008)","journal-title":"IEEE Trans. Signal Process."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11760-018-1250-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-018-1250-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-018-1250-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T00:49:30Z","timestamp":1660524570000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11760-018-1250-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,28]]},"references-count":46,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["1250"],"URL":"https:\/\/doi.org\/10.1007\/s11760-018-1250-8","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,28]]},"assertion":[{"value":"19 March 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 January 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 January 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}