{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:51:48Z","timestamp":1743061908562,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":27,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642200380"},{"type":"electronic","value":"9783642200397"}],"license":[{"start":{"date-parts":[[2011,1,1]],"date-time":"2011-01-01T00:00:00Z","timestamp":1293840000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011]]},"DOI":"10.1007\/978-3-642-20039-7_14","type":"book-chapter","created":{"date-parts":[[2011,4,16]],"date-time":"2011-04-16T07:37:49Z","timestamp":1302939469000},"page":"137-148","source":"Crossref","is-referenced-by-count":0,"title":["Mining Latent Sources of Causal Time Series Using Nonlinear State Space Modeling"],"prefix":"10.1007","author":[{"given":"Wei-Shing","family":"Chen","sequence":"first","affiliation":[]},{"given":"Fong-Jung","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"#cr-split#-14_CR1.1","unstructured":"Makridakis, S.: Time series prediction: Forecasting the future and understanding the past. In: Weigend, A.S., Gershenfeld, N.A. (eds.), p. 643. Addison-Wesley Publishing Company, Reading (1993), ISBN 0-201-62"},{"key":"#cr-split#-14_CR1.2","doi-asserted-by":"crossref","unstructured":"International Journal of Forecasting 10, 463-466 (1994)","DOI":"10.1111\/j.1752-0118.1994.tb00678.x"},{"key":"14_CR2","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.jbi.2009.11.002","volume":"43","author":"X. Hu","year":"2010","unstructured":"Hu, X., Xu, P., Wu, S., Asgari, S., Bergsneider, M.: A data mining framework for time series estimation. Journal of Biomedical Informatics\u00a043, 190\u2013199 (2010)","journal-title":"Journal of Biomedical Informatics"},{"key":"14_CR3","volume-title":"Linear System Theory and Design","author":"C.T. Chen","year":"1999","unstructured":"Chen, C.T.: Linear System Theory and Design, 3rd edn. Oxford University Press, New York (1999)","edition":"3"},{"key":"14_CR4","volume-title":"Applied Multivariate Data Analysis","author":"B.S. Everitt","year":"1992","unstructured":"Everitt, B.S., Dunn, G.: Applied Multivariate Data Analysis. Oxford University Press, New York (1992)"},{"key":"14_CR5","volume-title":"Bayesian Forecasting and Dynamic Models","author":"M. West","year":"1990","unstructured":"West, M., Harrison, J.: Bayesian Forecasting and Dynamic Models. Springer, New York (1990)"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"De Jong, P.: The diffuse Kalman filter Annals of Statistics 19 (1991)","DOI":"10.1214\/aos\/1176348139"},{"key":"14_CR7","volume-title":"Optimal filtering","author":"B.D.D. Anderson","year":"1979","unstructured":"Anderson, B.D.D., Moore, J.B.: Optimal filtering. Prentice-Hall, Englewood Cliffs (1979)"},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1109\/TNN.2004.826129","volume":"15","author":"A. Ilin","year":"2004","unstructured":"Ilin, A., Valpola, H., Oja, E.: Nonlinear dynamical factor analysis for state change detection. IEEE Transactions on Neural Networks\u00a015, 559\u2013575 (2004)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"14_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4613-0465-4","volume-title":"Subspace Identification for Linear Systems: Theory, Implementation Applications","author":"P.V. Overschee","year":"1996","unstructured":"Overschee, P.v., Moor, B.D.: Subspace Identification for Linear Systems: Theory, Implementation Applications. Springer, Heidelberg (1996)"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Quach, M., Brunel, N., d\u2019Alch\u00e9-Buc, F.: Estimating parameters and hidden variables in nonlinear state-space models based on ODEs for biological networks inference. Bioinformatics (2007)","DOI":"10.1093\/bioinformatics\/btm510"},{"key":"14_CR11","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/978-1-4471-0443-8_6","volume-title":"Advances in Independent Component Analysis","author":"H. Lappalainen","year":"2000","unstructured":"Lappalainen, H., Honkela, A.: Bayesian Nonlinear Independent Component Analysis by Multi-Layer Perceptrons. In: Girolami, M. (ed.) Advances in Independent Component Analysis, pp. 93\u2013121. Springer, Heidelberg (2000)"},{"key":"14_CR12","doi-asserted-by":"publisher","first-page":"2647","DOI":"10.1162\/089976602760408017","volume":"14","author":"H. Valpola","year":"2002","unstructured":"Valpola, H., Karhunen, J.: An unsupervised ensemble learning method for nonlinear dynamic state-space models. Neural Comput.\u00a014, 2647\u20132692 (2002)","journal-title":"Neural Comput."},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Giannakopoulos, X., Valpola, H.: Nonlinear dynamical factor analysis. In: Bayesian Inference And Maximum Entropy Methods in Science And Engineering: 20th International Workshop. AIP Conference Proceedings, vol.\u00a0568 (2001)","DOI":"10.1063\/1.1381895"},{"volume-title":"Ensemble learning in Bayesian neural networks","year":"1998","key":"14_CR14","unstructured":"Barber, D., Bishop, C. (eds.): Ensemble learning in Bayesian neural networks. Springer, Berlin (1998)"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Giannakopoulos, X., Valpola, H.: Nonlinear dynamical factor analysis. In: AIP Conference Proceedings, vol.\u00a0568, p. 305 (2001)","DOI":"10.1063\/1.1381895"},{"key":"14_CR16","unstructured":"Honkela, A., Valpola, H.: Unsupervised variational Bayesian learning of nonlinear models. In: Saul, L.K., Weis, Y., Bottou, L. (eds.) Advances in Neural Information Processing Systems (NIPS 2004), vol.\u00a017, pp. 593\u2013600 (2005)"},{"key":"14_CR17","unstructured":"Valpola, H., Honkela, A., Giannakopoulos, X.: Matlab Codes for the NFA and NDFA Algorithms (2002), http:\/\/www.cis.hut.fi\/projects\/bayes\/"},{"key":"14_CR18","series-title":"LNM","first-page":"366","volume-title":"Detecting strange attractors in turbulence","author":"F. Takens","year":"1981","unstructured":"Takens, F.: Detecting strange attractors in turbulence. LNM, vol.\u00a0898, pp. 366\u2013381. Springer, Heidelberg (1981)"},{"key":"14_CR19","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1103\/PhysRevA.33.1134","volume":"33","author":"A.M. Fraser","year":"1986","unstructured":"Fraser, A.M., Swinney, H.L.: Independent coordinates for strange attractors from mutual information. Physical Review A\u00a033, 1134 (1986)","journal-title":"Physical Review A"},{"key":"14_CR20","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198508397.001.0001","volume-title":"Chaos and Time Series Analysis","author":"J.C. Sprott","year":"2003","unstructured":"Sprott, J.C.: Chaos and Time Series Analysis, vol.\u00a0507. Oxford University Press, Oxford (2003)"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Naik, G.R., Kumar, D.K.: Determining Number of Independent Sources in Undercomplete Mixture. EURASIP Journal on Advances in Signal Processing\u00a05, Article ID 694850 (2009), doi:10.1155\/2009\/694850","DOI":"10.1155\/2009\/694850"},{"key":"14_CR22","unstructured":"G\u00e4vert, H., Hurri, J., S\u00e4rel\u00e4, J., Hyv\u00e4rinen, A.: FastICA Package (2005), http:\/\/www.cis.hut.fi\/projects\/ica\/fastica\/code\/dlcode.shtml"},{"key":"14_CR23","doi-asserted-by":"publisher","first-page":"2083","DOI":"10.1109\/78.847792","volume":"48","author":"R. Everson","year":"2000","unstructured":"Everson, R., Roberts, S.: Inferring the eigenvalues of covariance matrices from limited, noisy data. IEEE Transactions on Signal Processing\u00a048, 2083\u20132091 (2000)","journal-title":"IEEE Transactions on Signal Processing"},{"key":"14_CR24","doi-asserted-by":"crossref","unstructured":"Santos, J.e.D.A., Barreto, G.A., Medeiros, C.a.M.S.: Estimating the Number of Hidden Neurons of the MLP Using Singular Value Decomposition and Principal Components Analysis: A Novel Approach. In: 2010 Eleventh Brazilian Symposium on Neural Networks, pp. 19\u201324 (2010)","DOI":"10.1109\/SBRN.2010.12"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Honkela, A.: Approximating Nonlinear Transformations of Probability Distributions for Nonlinear Independent Component Analysis. In: Proceedings of the 2004 IEEE International Joint Conference on Neural Networks (IJCNN 2004), Budapest, Hungary, pp. 2169\u20132174 (2004)","DOI":"10.1109\/IJCNN.2004.1380955"},{"key":"14_CR26","doi-asserted-by":"crossref","unstructured":"Chen, W.-S.: Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series. Physica A: Statistical Mechanics and its Applications (in Press, 2011), doi:10.1016\/j.physa.2010.12.020","DOI":"10.1016\/j.physa.2010.12.020"}],"container-title":["Lecture Notes in Computer Science","Intelligent Information and Database Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-20039-7_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T03:38:32Z","timestamp":1741145912000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-20039-7_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011]]},"ISBN":["9783642200380","9783642200397"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-20039-7_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2011]]}}}