{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,11]],"date-time":"2026-11-11T07:11:53Z","timestamp":1794381113385,"version":"4.9.0"},"publisher-location":"Berlin, Heidelberg","reference-count":14,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783540228813","type":"print"},{"value":"9783540286516","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2004]]},"DOI":"10.1007\/978-3-540-28651-6_101","type":"book-chapter","created":{"date-parts":[[2010,9,16]],"date-time":"2010-09-16T16:04:40Z","timestamp":1284653080000},"page":"684-689","source":"Crossref","is-referenced-by-count":1,"title":["Local Separation Property of the Two-Source ICA Problem with the One-Bit-Matching Condition"],"prefix":"10.1007","author":[{"given":"Jinwen","family":"Ma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiyong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"issue":"7","key":"101_CR1","doi-asserted-by":"publisher","first-page":"2461","DOI":"10.1109\/78.224254","volume":"41","author":"L. Tong","year":"1993","unstructured":"Tong, L., Inouye, Y., Liu, R.: Waveform-preserving blind estimation of multiple independent sources. IEEE Trans. on Signal Processing\u00a041(7), 2461\u20132470 (1993)","journal-title":"IEEE Trans. on Signal Processing"},{"key":"101_CR2","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/0165-1684(94)90029-9","volume":"36","author":"P. Comon","year":"1994","unstructured":"Comon, P.: Independent component analysis\u2013a new concept? Signal Processing\u00a036, 287\u2013314 (1994)","journal-title":"Signal Processing"},{"key":"101_CR3","doi-asserted-by":"publisher","first-page":"1129","DOI":"10.1162\/neco.1995.7.6.1129","volume":"7","author":"A. Bell","year":"1995","unstructured":"Bell, A., Sejnowski, T.: An information-maximization approach to blind separation and blind deconvolution. Neural Computation\u00a07, 1129\u20131159 (1995)","journal-title":"Neural Computation"},{"key":"101_CR4","first-page":"757","volume":"8","author":"S.I. Amari","year":"1996","unstructured":"Amari, S.I., Cichocki, A., Yang, H.: A new learning algorithm for blind separation of sources. Advances in Neural Information Processing\u00a08, 757\u2013763 (1996)","journal-title":"Advances in Neural Information Processing"},{"key":"101_CR5","first-page":"97","volume-title":"Proc. of Int. ICSC Workshop on Independence and Artificial Neural Networks (I&ANN 1998)","author":"E. Oja","year":"1998","unstructured":"Oja, E.: ICA learning rules: stationarity,stability, and sigmoids. In: Fyfe, C. (ed.) Proc. of Int. ICSC Workshop on Independence and Artificial Neural Networks (I&ANN 1998), Tenerife, Spain, Febraury 9-10, pp. 97\u2013103. ICSC Acadenic Press, New York (1998)"},{"key":"101_CR6","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/97.566704","volume":"4","author":"J.F. Cardoso","year":"1999","unstructured":"Cardoso, J.F.: Infomax and maximum likelihood for source separation. IEEE Signal Processing Letters\u00a04, 112\u2013114 (1999)","journal-title":"IEEE Signal Processing Letters"},{"key":"101_CR7","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/S0925-2312(98)00050-2","volume":"22","author":"L. Xu","year":"1998","unstructured":"Xu, L., Cheung, C.C., Amari, S.I.: Learned parametric mixture based ica algorithm. Neurocomputing\u00a022, 69\u201380 (1998)","journal-title":"Neurocomputing"},{"key":"101_CR8","unstructured":"Xu, L., Cheung, C.C., Amari, S.I.: Further results on nonlinearity and separation capability of a linear mixture ICA method and learned LPM. In: Fyfe, C. (ed.) Proceedings of the I&ANN 1998, pp. 39\u201345 (1998)"},{"key":"101_CR9","doi-asserted-by":"publisher","first-page":"2103","DOI":"10.1162\/089976698300016981","volume":"10","author":"M. Girolami","year":"1998","unstructured":"Girolami, M.: An alternative perspective on adaptive independent component analysis algorithms. Neural Computation\u00a010, 2103\u20132114 (1998)","journal-title":"Neural Computation"},{"key":"101_CR10","doi-asserted-by":"publisher","first-page":"1957","DOI":"10.1162\/089976699300016043","volume":"11","author":"R. Everson","year":"1999","unstructured":"Everson, R., Roberts, S.: Independent component analysis: A flexible nonlinearity and decorrelating manifold approach. Neural Computation\u00a011, 1957\u20131983 (1999)","journal-title":"Neural Computation"},{"key":"101_CR11","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1162\/089976699300016719","volume":"11","author":"T.W. Lee","year":"1999","unstructured":"Lee, T.W., Girolami, M., Sejnowski, T.J.: Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Computation\u00a011, 417\u2013441 (1999)","journal-title":"Neural Computation"},{"key":"101_CR12","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1162\/089976601300014510","volume":"13","author":"M. Welling","year":"2001","unstructured":"Welling, M., Weber, M.: A constrained EM algorithm for independent component analysis. Neural Computation\u00a013, 677\u2013689 (2001)","journal-title":"Neural Computation"},{"key":"101_CR13","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/S0925-2312(99)00118-6","volume":"30","author":"C.C. Cheung","year":"2000","unstructured":"Cheung, C.C., Xu, L.: Some global and local convergence analysis on the information-theoretic independent component analysis approach. Neurocomputing\u00a030, 79\u2013102 (2000)","journal-title":"Neurocomputing"},{"key":"101_CR14","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1162\/089976604322742074","volume":"16","author":"Z.Y. Liu","year":"2004","unstructured":"Liu, Z.Y., Chiu, K.C., Xu, L.: One-bit-matching conjecture for independent component analysis. Neural Computation\u00a016, 383\u2013399 (2004)","journal-title":"Neural Computation"}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2004"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-28651-6_101.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,2]],"date-time":"2021-05-02T23:33:16Z","timestamp":1619998396000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-28651-6_101"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004]]},"ISBN":["9783540228813","9783540286516"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-28651-6_101","relation":{"is-part-of":[{"id-type":"doi","id":"https:\/\/doi.org\/10.1007\/b99975","asserted-by":"object"}]},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2004]]}}}