{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T05:10:04Z","timestamp":1716786604926},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2014,5,31]],"date-time":"2014-05-31T00:00:00Z","timestamp":1401494400000},"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":["Appl Intell"],"published-print":{"date-parts":[[2014,9]]},"DOI":"10.1007\/s10489-014-0548-7","type":"journal-article","created":{"date-parts":[[2014,5,30]],"date-time":"2014-05-30T01:54:39Z","timestamp":1401414879000},"page":"594-605","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["LTI ODE-valued neural networks"],"prefix":"10.1007","volume":"41","author":[{"given":"Manel","family":"Velasco","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enric X.","family":"Mart\u00edn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cecilio","family":"Angulo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pau","family":"Mart\u00ed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,5,31]]},"reference":[{"key":"548_CR1","doi-asserted-by":"crossref","unstructured":"Aoyagi T, Radenamad D, Nakano Y, Hirose A (2010) Complex-valued self-organizing map clustering using complex inner product in active millimeter-wave imaging. In: The 2010 International Joint Conference on Neural Networks (IJCNN), pp 1\u20136","DOI":"10.1109\/IJCNN.2010.5596854"},{"key":"548_CR2","unstructured":"Arena P, Fortuna L, Occhipinti L, Xibilia M (1994) Neural networks for quaternion-valued function approximation. In: Circuits and Systems, 1994. ISCAS \u201994., 1994 IEEE International Symposium, vol 6, pp 307\u2013310"},{"issue":"7","key":"548_CR3","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1016\/j.neunet.2008.03.004","volume":"21","author":"S Buchholz","year":"2008","unstructured":"Buchholz S, Sommer G (2008) On Clifford neurons and Clifford multi\u2013layer perceptrons. Neural Netw 21(7):925\u2013935","journal-title":"Neural Netw"},{"issue":"8","key":"548_CR4","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1109\/TNN.2011.2157358","volume":"22","author":"B Che Ujang","year":"2011","unstructured":"Che Ujang B, Took C, Mandic D (2011) Quaternion-valued nonlinear adaptive filtering. Neural Netw IEEE Trans 22(8):1193\u20131206. doi: 10.1109\/TNN.2011.2157358","journal-title":"Neural Netw IEEE Trans"},{"issue":"16\u201318","key":"548_CR5","doi-asserted-by":"crossref","first-page":"3421","DOI":"10.1016\/j.neucom.2007.12.003","volume":"71","author":"S Chen","year":"2008","unstructured":"Chen S, Hong X, Harris CJ, Hanzo L (2008) Fully complex-valued radial basis function networks: orthogonal least squares regression and classification. Neurocomputing 71(16\u201318):3421\u20133433. doi: 10.1016\/j.neucom.2007.12.003","journal-title":"Neurocomputing"},{"key":"548_CR6","volume-title":"Feedback control of dynamic systems, 4th edn","author":"GF Franklin","year":"2001","unstructured":"Franklin GF, Powell DJ, Emami-Naeini A (2001) Feedback control of dynamic systems, 4th edn. Prentice Hall PTR, Upper Saddle River, NJ"},{"key":"548_CR7","doi-asserted-by":"crossref","unstructured":"Hirose A (2006) Complex-valued neural networks. In: Studies in computational intelligence, vol 32. Springer","DOI":"10.1007\/978-3-540-33457-6"},{"key":"548_CR8","doi-asserted-by":"crossref","unstructured":"Hirose A (2009) Complex-valued neural networks: the merits and their origins. In: International joint conference on neural networks, 1999. IJCNN99. IEEE, Atlanta, Georgia, USA, pp 1237\u20131244","DOI":"10.1109\/IJCNN.2009.5178754"},{"key":"548_CR9","first-page":"42","volume-title":"Recent progress in applications of complex-valued neural networks. In: Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II, ICAISC\u201910","author":"A Hirose","year":"2010","unstructured":"Hirose A (2010) Recent progress in applications of complex-valued neural networks. In: Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II, ICAISC\u201910. Springer-Verlag, Berlin, pp 42\u201346"},{"key":"548_CR10","doi-asserted-by":"crossref","unstructured":"Hirose A (2012) Complex-valued neural networks. In: Studies in computational intelligence, vol 400. Springer","DOI":"10.1007\/978-3-642-27632-3"},{"key":"548_CR11","volume-title":"Neural information processing - 18th international conference, ICONIP 2011, Part I, Lecture notes in computer science, vol 7062, pp 526\u2013531","author":"A Hirose","year":"2011","unstructured":"Hirose A, Yoshida S (2011) Comparison of complex- and real-valued feedforward neural networks in their generalization ability. In: Lu BL, Zhang L, Kwok JT (eds) Neural information processing - 18th international conference, ICONIP 2011, Part I, Lecture notes in computer science, vol 7062, pp 526\u2013531. Springer, Shanghai"},{"issue":"4","key":"548_CR12","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1109\/TNNLS.2012.2183613","volume":"23","author":"A Hirose","year":"2012","unstructured":"Hirose A, Yoshida S (2012) Generalization characteristics of complex-valued feedforward neural networks in relation to signal coherence. IEEE Trans Neural Netw Learn Syst 23(4):541\u2013551","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"6","key":"548_CR13","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1109\/TNNLS.2012.2195028","volume":"23","author":"J Hu","year":"2012","unstructured":"Hu J, Wang J (2012) Global stability of complex-valued recurrent neural networks with time-delays. IEEE Trans Neural Netw Learn Syst 23(6):853\u2013865","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"6","key":"548_CR14","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1109\/TNN.2003.820440","volume":"14","author":"E Izhikevich","year":"2003","unstructured":"Izhikevich E (2003) Simple model of spiking neurons. IEEE Trans Neural Netw 14(6):1569\u20131572","journal-title":"IEEE Trans Neural Netw"},{"key":"548_CR15","doi-asserted-by":"crossref","unstructured":"Izhikevich EM (2006) Dynamical systems in neuroscience: the geometry of excitability and bursting (computational neuroscience), 1edn. The MIT Press","DOI":"10.7551\/mitpress\/2526.001.0001"},{"key":"548_CR16","unstructured":"Kuroe Y, Tanigawa S, Iima H (2011). In: Lu BL, Zhang L, Kwok JT (eds) Neural information processing - 18th international conference, ICONIP 2011, Part I, Lecture Notes in Computer Science, vol 7062. Springer, Shanghai, pp 560\u2013569"},{"issue":"1","key":"548_CR17","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s10489-013-0447-3","volume":"40","author":"P Li","year":"2014","unstructured":"Li P, Xiao H (2014) Model and algorithm of quantum-inspired neural network with sequence input based on controlled rotation gates. Appl Intell 40(1):107\u2013126. doi: 10.1007\/s10489-013-0447-3","journal-title":"Appl Intell"},{"key":"548_CR18","doi-asserted-by":"crossref","DOI":"10.1002\/047084535X","volume-title":"Recurrent neural networks for prediction: learning algorithms, architectures and aStability","author":"DP Mandic","year":"2001","unstructured":"Mandic DP, Chambers J (2001) Recurrent neural networks for prediction: learning algorithms, architectures and aStability. Wiley, New York"},{"key":"548_CR19","doi-asserted-by":"crossref","DOI":"10.4018\/978-1-60566-214-5","volume-title":"Complex-valued neural networks: utilizing high-dimensional parameters. Information science reference","author":"T Nitta","year":"2009","unstructured":"Nitta T (2009) Complex-valued neural networks: utilizing high-dimensional parameters. Information science reference. Imprint of: IGI Publishing, Hershey"},{"key":"548_CR20","unstructured":"Pearson JK (1995) Clifford networks. Ph.D. thesis, University of Kent"},{"issue":"4","key":"548_CR21","doi-asserted-by":"crossref","first-page":"409","DOI":"10.55782\/ane-2011-1862","volume":"71","author":"F Ponulak","year":"2011","unstructured":"Ponulak F, Kasinski A (2011) Introduction to spiking neural networks: Information processing, learning and applications. Acta Neurobiol Exp (Wars) 71(4):409\u201333","journal-title":"Acta Neurobiol Exp (Wars)"},{"issue":"1","key":"548_CR22","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.neunet.2004.08.002","volume":"18","author":"SSP Rattan","year":"2005","unstructured":"Rattan SSP, Hsieh WW (2005) Complex-valued neural networks for nonlinear complex principal component analysis. Neural Netw 18(1):61\u201369. doi: 10.1016\/j.neunet.2004.08.002","journal-title":"Neural Netw"},{"issue":"1","key":"548_CR23","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.neucom.2011.05.036","volume":"78","author":"R Savitha","year":"2012","unstructured":"Savitha R, Suresh S, Sundararajan N, Kim H (2012) A fully complex-valued radial basis function classifier for real-valued classification problems. Neurocomputing 78(1):104\u2013110. doi: 10.1016\/j.neucom.2011.05.036","journal-title":"Neurocomputing"},{"key":"548_CR24","doi-asserted-by":"crossref","unstructured":"Sheikhan M (2014) Generation of suprasegmental information for speech using a recurrent neural network and binary gravitational search algorithm for feature selection. Appl Intell:1\u201319. doi: 10.1007\/s10489-013-0505-x","DOI":"10.1007\/s10489-013-0505-x"},{"key":"548_CR25","unstructured":"Velasco M, Mart\u00edn EX, Angulo C, Mart\u00ed P (2013) LTI ODE-valued neuronal networks: solving multiple problems using a single network structure. Research report ESAII-RR-13-01, Automatic Control Department, Technical University of Catalonia"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-014-0548-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10489-014-0548-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-014-0548-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T04:51:30Z","timestamp":1716785490000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10489-014-0548-7"}},"subtitle":["Multiple problem solving using a single neural structure"],"short-title":[],"issued":{"date-parts":[[2014,5,31]]},"references-count":25,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2014,9]]}},"alternative-id":["548"],"URL":"https:\/\/doi.org\/10.1007\/s10489-014-0548-7","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,5,31]]}}}