{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T22:45:00Z","timestamp":1775083500525,"version":"3.50.1"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030269791","type":"print"},{"value":"9783030269807","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-26980-7_27","type":"book-chapter","created":{"date-parts":[[2019,8,18]],"date-time":"2019-08-18T23:03:04Z","timestamp":1566169384000},"page":"261-270","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Toeplitz Hermitian Positive Definite Matrix Machine Learning Based on Fisher Metric"],"prefix":"10.1007","author":[{"given":"Yann","family":"Cabanes","sequence":"first","affiliation":[]},{"given":"Fr\u00e9d\u00e9ric","family":"Barbaresco","sequence":"additional","affiliation":[]},{"given":"Marc","family":"Arnaudon","sequence":"additional","affiliation":[]},{"given":"J\u00e9r\u00e9mie","family":"Bigot","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,2]]},"reference":[{"issue":"3","key":"27_CR1","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.1137\/15M102112X","volume":"37","author":"B. Jeuris","year":"2016","unstructured":"Jeuris, B., Vandrebril, R.: The K\u00e4hler mean of Block-Toeplitz matrices with Toeplitz structured blocks (2016)","journal-title":"SIAM Journal on Matrix Analysis and Applications"},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Chevallier, E., Forget, T., Barbaresco, F., Angulo, J.: Kernel Density Estimation on the Siegel Space with an Application to Radar Processing. Entropy (2016)","DOI":"10.3390\/e18110396"},{"key":"27_CR3","unstructured":"Haykin, S.: Adaptive Filter Theory. Pearson (2014)"},{"issue":"4","key":"27_CR4","first-page":"595","volume":"7","author":"M Arnaudon","year":"2013","unstructured":"Arnaudon, M., Barbaresco, F., Yang, L.: Riemannian medians and means with applications to radar signal processing. IEEE J. 7(4), 595\u2013604 (2013)","journal-title":"IEEE J."},{"key":"27_CR5","unstructured":"Barbaresco, F.: Super resolution spectrum analysis regularization: burg, capon and AGO-antagonistic algorithms. In: EUSIPCO 1996, Trieste, Italy, pp. 2005\u20132008 (1996)"},{"key":"27_CR6","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-642-30232-9_9","volume-title":"Matrix Information Geometry","author":"F Barbaresco","year":"2012","unstructured":"Barbaresco, F.: Information geometry of covariance matrix: cartan-siegel homogeneous bounded domains, mostow\/berger fibration and fr\u00e9chet median. In: Nielsen, F., Bhatia, R. (eds.) Matrix Information Geometry, pp. 199\u2013256. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-30232-9_9"},{"key":"27_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-52844-0","volume-title":"Encyclopedia of Distances","author":"MM Deza","year":"2016","unstructured":"Deza, M.M., Deza, E.: Encyclopedia of Distances. Springer, Heidelberg (2016). https:\/\/doi.org\/10.1007\/978-3-662-52844-0. ISBN 978-3-662-52844-0. http:\/\/www.springer.com\/us\/book\/9783662528433"},{"issue":"1","key":"27_CR8","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/s10543-013-0450-4","volume":"54","author":"D Bini","year":"2014","unstructured":"Bini, D., Iannazzo, B., Jeuris, B., Vandebril, R.: Geometric means of structured matrices. BIT 54(1), 55\u201383 (2014)","journal-title":"BIT"},{"key":"27_CR9","volume-title":"Low-Angle Radar Land Clutter, Measurements and Empirical Models","author":"J Barrie Billingsley","year":"2002","unstructured":"Barrie Billingsley, J.: Low-Angle Radar Land Clutter, Measurements and Empirical Models. William Andrew Publishing, Norwich (2002)"},{"key":"27_CR10","unstructured":"Greco, M.S., Gini, F.: Radar Clutter Modeling"},{"key":"27_CR11","unstructured":"Arnaudon, M., Barbaresco, F., Yang, L.: Riemannian medians and means with applications to radar signal processing. IEEE Trans. Sig. Proc."},{"issue":"1","key":"27_CR12","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1049\/iet-rsn.2016.0042","volume":"11","author":"A Decurninge","year":"2016","unstructured":"Decurninge, A., Barbaresco, F.: Robust burg estimation of radar scatter matrix for mixtures of gaussian stationary autoregressive vectors. IET Radar Sonar Navig. 11(1), 78\u201389 (2016)","journal-title":"IET Radar Sonar Navig."},{"key":"27_CR13","doi-asserted-by":"crossref","unstructured":"Barbaresco, F., Forget, T., Chevallier, E., Angulo, J.: Doppler spectrum segmentation of radar sea clutter by mean-shift and information geometry metric (2017)","DOI":"10.1109\/IRS.2016.7497314"},{"key":"27_CR14","doi-asserted-by":"crossref","unstructured":"Barbaresco, F.: Radar micro-doppler signal encoding in siegel unit poly-disk for machine learning in fisher metric space. In: IRS 2018, Bonn, June 2018","DOI":"10.23919\/IRS.2018.8448021"}],"container-title":["Lecture Notes in Computer Science","Geometric Science of Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-26980-7_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:03:52Z","timestamp":1710266632000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-26980-7_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030269791","9783030269807"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-26980-7_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"2 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"GSI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Geometric Science of Information","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toulouse","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"gsi2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.see.asso.fr\/GSI2019","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}