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“综合电子信息系统”科技部国际科技合作基地首届国际学术研讨会
时间:2019-08-01 11:02   点击:   所属单位:电子工程学院
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“综合电子信息系统”科技部国际科技合作基地首届国际学术研讨会(International Symposium on Multi-modal Sensing and Information Processing, ISMSIP 2019)定于8月4 - 5日在西安志诚丽柏酒店20楼会议室举行。大会邀请到来自美国和英国著名高校的IEEE Fellow等多位相关领域知名专家学者做特邀报告。
会议网址
https://meeting.xidian.edu.cn/symposium/ismsip2019/
论坛免费向国内外同行开放,不收取会议费。会议期间食宿自理。
会议主办单位:西安电子科技大学
会议联系人:刘婧,15929955180
西安电子科技大学
         2019年8月   
International Symposium on Multi-modal Sensing and Information Processing 2019
ISMSIP2019 Schedule
Venue: Ziction Liberal Hotel, 20th floor Conference Room
https://meeting.xidian.edu.cn/symposium/ismsip2019/
Aug 4  Morning
08:30-09:00 Opening Ceremony  
09:00-09:40 Introduction to Decomposition Based Multiobjective Evolutionary Computation Qingfu ZHANG
09:40-10:20 3D Modeling Technology for Cultural Heritage Protection and Smart City Xianfeng HUANG
Tea break(20min)
10:40-11:20 Graph signal processing: fundamentals and distributed algorithms Junzheng JIANG
11:20-12:00 Deep Learning With Applications To Radar Target Detection and Recognition Lan DU
Lunch time
 Aug 4  Afternoon
14:30-15:10 The Tail-null-space-property and the Stability of the Tail-minimization Approach in Compressed Sensing with or without Frames Shidong LI
15:10-15:50 Sparse Bayesian Algorithms for Signal Recovery Ningning HAN
15:50-16:30 Infinite-Dimensional Compressed Sensing and Spectral Analysis of Signals Zai YANG
Tea break(20min)
16:50-17:30 Transmit Signal Design for Large-Scale MIMO System With One-Bit DACs Bin LIAO
17:30-18:10 From Random Vectors to Random Matrices: Asymptotics of Empirical Eigenvalues for Large Separable Covariance Matrices TieBin MI
Aug 5  Morning
08:30-09:10 Defect-Detecting Technology for over 100-meter-Shaft under the Disaster Luliang TANG
09:10-09:50 Area Coverage and Target Tracking for Mobile sensor networks Gang WANG
Tea break(20min)
10:10-10:50 A Fast Implementation of Interactive Multi-Model Generalized Labeled Multi-Bernoulli Filter for Interval Measurements Sunyong WU
10:50-11:30 Sparse Frame DOA Estimations via Rand-one Correlation Model for Low SNR and Limited Snapshots Cao ZENG

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