{"id":150000,"date":"1995-01-01T00:00:00","date_gmt":"1995-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/recent-progress-in-the-measurement-and-analysis-of-ece-on-jet\/"},"modified":"2018-10-16T21:53:59","modified_gmt":"2018-10-17T04:53:59","slug":"recent-progress-in-the-measurement-and-analysis-of-ece-on-jet","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/recent-progress-in-the-measurement-and-analysis-of-ece-on-jet\/","title":{"rendered":"Recent Progress in the Measurement and Analysis of ECE on JET"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Recent changes to the JET ECE diagnostic system have been made to accommodate the changing requirements of JET and to enhance further the measurement performance of the broad-band heterodyne radiometer. The radiometer frequency coverage has been extended, its spatial resolution has been improved and a technique for frequency selective sharing of radiation among its six mixers has been developed. An analysis of the limiting resolution of ECE measurements has been made, and applied to the determination of the optimum IF filter widths for the radiometer. These improvements and the resolution analysis are described, and some illustrative results are shown. A study of the feasibility of using neural networks to reduce the level of systematic uncertainty in the JET ECE data has been completed. The technique and the results are presented.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Recent changes to the JET ECE diagnostic system have been made to accommodate the changing requirements of JET and to enhance further the measurement performance of the broad-band heterodyne radiometer. The radiometer frequency coverage has been extended, its spatial resolution has been improved and a technique for frequency selective sharing of radiation among its six [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-150000","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 9th International Workshop on ECE 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