報名開始時間:2019-11-17 23:51:24
報名結束時間:2019-11-22 16:00:00
目前報名活動時間已結束!
活動資訊: 毫米波5G通訊及雷達感測社群活動: 深度學習之認知雷達設計與電波散射特性分析
主講人: 陳信宏博士 中山科學院研究員![](/images/ckfinder/images/3/20191118075229.jpg)
林昇洲博士 輔仁大學電機系
時間: 108.11.22 (五)19:00-21:30
地點: SF736
經費來源: 深耕計畫
餐點: PIZZA and Drink
計畫召集人: 林昇洲 主任
報名網址 : http://www.ee.fju.edu.tw/signup.php?tpl=3&type=signup&id=3051
![「radar cross section」的圖片搜尋結果](https://www.ansys.com/-/media/ansys/corporate/examples/products/rcs-scattering.jpg?h=200&la=en&w=300&hash=BC1A0DC9BC83391BF28F68A99803863209C4AB88)
陳信宏博士
學歷:國立台灣大學 電機學士、碩士、博士
專長:雷達截面積(RCS) 技術開發與應用、目標雷達回波特徵模擬
簡介:
![「認知雷達」的圖片搜尋結果](data:image/jpeg;base64,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)
![「deep learning radar」的圖片搜尋結果](data:image/png;base64,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)
下載檔案 - 深度學習之認知雷達設計與電波散射特性分析.pdf
報名結束時間:2019-11-22 16:00:00
目前報名活動時間已結束!
活動資訊: 毫米波5G通訊及雷達感測社群活動: 深度學習之認知雷達設計與電波散射特性分析
主講人: 陳信宏博士 中山科學院研究員
![](/images/ckfinder/images/3/20191118075229.jpg)
林昇洲博士 輔仁大學電機系
地點: SF736
經費來源: 深耕計畫
餐點: PIZZA and Drink
計畫召集人: 林昇洲 主任
報名網址 : http://www.ee.fju.edu.tw/signup.php?tpl=3&type=signup&id=3051
![「radar cross section」的圖片搜尋結果](https://www.ansys.com/-/media/ansys/corporate/examples/products/rcs-scattering.jpg?h=200&la=en&w=300&hash=BC1A0DC9BC83391BF28F68A99803863209C4AB88)
陳信宏博士
學歷:國立台灣大學 電機學士、碩士、博士
專長:雷達截面積(RCS) 技術開發與應用、目標雷達回波特徵模擬
簡介:
- 認知雷達是一種新的具備獨特性能和驚人能力的下一代雷達典範,它被設想成具備智能化的處理能力以實現知識的關聯。認知雷達最早由Haykin和Guerci提出,在過去幾年間已經吸引了大量雷達領域專家的關注。
- 主要觀點是去模仿人類的大腦及其他具有回聲定位能力的動物,如蝙蝠、海豚、鯨魚。它們的對周圍環境刺激的反應過程總結為如下四個步驟:感知、記憶、聚焦和智能。智能的概念是上述提及的四個功能中最難描述的。
- 雷達目標識別技術是人工智慧在裝備領域的重要應用,隨著人工智慧技術的發展,雷達識別也在不斷進步,從模式識別、機器學習到近年來的發展迅猛的深度學習、遷移學習等在雷達識別中都有較多研究成果。
- 傳統目標識別存在的主要問題是按照預先設定的識別模式工作,不具備隨目標和環境變化而自動改變識別模式的能力,對目和環境的適應能力不足。面對日益複雜的環境及密集雜波、多目標背景等挑戰,為滿足當前特別是未來作戰需求,識別技術必須進一步創新發展以不斷提升識別模式、識別性能,才能適應日益複雜的環境。
![「deep learning radar」的圖片搜尋結果](https://d3i71xaburhd42.cloudfront.net/9fc9917a97886457455bd30fd629554c7be4995e/2-Figure1-1.png)
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