{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:13:57Z","timestamp":1740132837388,"version":"3.37.3"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2017,5,1]],"date-time":"2017-05-01T00:00:00Z","timestamp":1493596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/100010219","name":"Naval Undersea Warfare Center","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2017,5,1]]},"DOI":"10.1109\/tsp.2017.2659645","type":"journal-article","created":{"date-parts":[[2017,1,25]],"date-time":"2017-01-25T19:25:48Z","timestamp":1485372348000},"page":"2455-2470","source":"Crossref","is-referenced-by-count":15,"title":["Uniform Manifold Sampling (UMS): Sampling the Maximum Entropy PDF"],"prefix":"10.1109","volume":"65","author":[{"given":"Paul M.","family":"Baggenstoss","sequence":"first","affiliation":[{"name":"Fraunhofer FKIE, Wachtberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/34.291440"},{"year":"2013","author":"conrad","article-title":"Probability distributions and maximum entropy","key":"ref32"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1002\/9781118428306"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/MAES.2004.1263230"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/TAES.2016.150285"},{"key":"ref34","first-page":"169","article-title":"Making large-scale SVM learning practical","author":"joachims","year":"1999","journal-title":"Advances in Kernel Methods—Support Vector Learning"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/PROC.1982.12425"},{"year":"1993","author":"kapur","journal-title":"Maximum Entropy Models in Science and Engineering","key":"ref11"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1137\/1.9780898717921"},{"year":"2005","author":"aster","journal-title":"Parameter Estimation and Inverse Problems","key":"ref13"},{"year":"1993","author":"kay","journal-title":"Fundamentals of Statisticsl Signal Processing Estimation Theory","key":"ref14"},{"year":"1992","author":"chan","article-title":"Performance of the Gibbs, hit-and-run, and metropolis samplers","key":"ref15"},{"year":"1957","author":"khincin","journal-title":"Mathematical Foundations of Information Theory","key":"ref16"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1145\/1921598.1921600"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1287\/opre.32.6.1296"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1145\/256562.256619"},{"year":"2006","author":"young","journal-title":"The HTK Book Version 3 4","key":"ref28"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/TSP.2015.2419189"},{"key":"ref27","first-page":"374","article-title":"Distance measures for speech recognition, psychological and instrumental","volume":"116","author":"mermelstein","year":"1976","journal-title":"Pattern Recognit Artif Intell"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TSP.2002.808109"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/89.917686"},{"key":"ref29","first-page":"2421","article-title":"Speech reconstruction from MEL-frequency cepstral coefficients using a source-filter model","author":"milner","year":"0","journal-title":"Proc Int Conf Spoken Lang Process"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1214\/aos\/1056562461"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1145\/2816795.2818100"},{"year":"2002","author":"lee","journal-title":"Introduction to Smooth Manifolds","key":"ref7"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1162\/neco.2006.18.7.1527"},{"year":"2013","author":"kay","key":"ref9"},{"year":"1999","author":"vapnik","journal-title":"The Nature of Statistical Learning","key":"ref1"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1214\/aos\/1056562461"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1190\/1.1440265"},{"year":"1981","author":"malik","article-title":"One and two dimensional maximum entropy spectral estimation","key":"ref21"},{"key":"ref24","first-page":"595","article-title":"A new algorithm for maximum entropy image reconstruction","volume":"12","author":"wei","year":"0","journal-title":"Proc IEEE Int Conf Acoust Speech Signal Process"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/TC.1977.1674845"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316726","author":"ripley","year":"1987","journal-title":"Stochastic Simulation"},{"year":"1988","author":"kay","journal-title":"Modern Spectral Estimation Theory and Applications","key":"ref25"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/7858803\/07833210.pdf?arnumber=7833210","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:27:54Z","timestamp":1642004874000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/7833210\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,1]]},"references-count":35,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tsp.2017.2659645","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"type":"print","value":"1053-587X"},{"type":"electronic","value":"1941-0476"}],"subject":[],"published":{"date-parts":[[2017,5,1]]}}}