{"id":2120,"date":"2017-02-20T15:16:00","date_gmt":"2017-02-20T06:16:00","guid":{"rendered":"http:\/\/cinetjp-static3.nict.go.jp\/english\/?post_type=event&#038;p=2120"},"modified":"2022-10-09T15:18:18","modified_gmt":"2022-10-09T06:18:18","slug":"20170220_1938","status":"publish","type":"event","link":"http:\/\/cinetjp-static3.nict.go.jp\/english\/event\/20170220_1938\/","title":{"rendered":"Mikio Hasegawa: \u201cNonlinear Mathematical Engineering on Wireless Communications\u201d"},"content":{"rendered":"\n<p>March 7, 2017\u3000\u300014:00&nbsp;\u301c&nbsp;15:00<\/p>\n\n\n\n<p>CiNet 1F Conference Room<\/p>\n\n\n\n<p>Mikio Hasegawa<\/p>\n\n\n\n<p>Professor<br>Tokyo University of Science<\/p>\n\n\n\n<p>Host :&nbsp;<a href=\"http:\/\/cinetjp-static3.nict.go.jp\/english\/people\/2014273\/\">Kenji Leibnitz&nbsp;<\/a>(PI)<\/p>\n\n\n\n<p><strong>Abstract:<\/strong><\/p>\n\n\n\n<p>This talk introduces various applications of nonlinear mathematical sciences to wireless communications field. Noise-induced synchronization phenomenon of nonlinear oscillators is applied to wireless sensor networks. Machine learning algorithms are applied to cognitive radio networks. Quantum neural networks are applied to optimization of cellular networks. Performances of the proposed schemes are verified with computer simulation results and several experimental results using real wireless communication systems.<\/p>\n","protected":false},"featured_media":0,"template":"","acf":[],"_links":{"self":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/english\/wp-json\/wp\/v2\/event\/2120"}],"collection":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/english\/wp-json\/wp\/v2\/event"}],"about":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/english\/wp-json\/wp\/v2\/types\/event"}],"wp:attachment":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/english\/wp-json\/wp\/v2\/media?parent=2120"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}