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Mixed-Integer Conic Relaxation for TOA-Based Multiple Source Localizaton

Time: May 27, 2019

地址 B301 meeting room in the New Technology Building of North Campus 事件时间: 2019-05-31 09:00:00

https://meeting.xidian.edu.cn/uploads/images/201905/1558940914.png

Title:

Mixed-Integer Conic Relaxation for TOA-Based Multiple Source Localizaton

Lecturer:

Prof. Anthony Man-Cho So

Time:

2019-05-31 09:00:00

Venue:

B301 meeting room in the New Technology Building of North Campus

Lecturer Profile

Anthony Man-Cho So received his BSE degree in Computer Science from Princeton University with minors in Applied and Computational Mathematics, Engineering and Management Systems, and German Language and Culture. He then received his MSc degree in Computer Science and his PhD degree in Computer Science with a PhD minor in Mathematics from Stanford University. Dr. So joined The Chinese University of Hong Kong (CUHK) in 2007. He currently serves as Assistant Dean of the Faculty of Engineering and is an Associate Professor in the Department of Systems Engineering and Engineering Management. He also holds a courtesy appointment as Associate Professor in the CUHK-BGI Innovation Institute of Trans-omics. His recent research focuses on the interplay between optimization theory and various areas of algorithm design, such as computational geometry, machine learning, signal processing, bioinformatics, and algorithmic game theory.

Lecture Abstract

Source localization is among the most fundamental and studied problems in signal processing. In this talk, we consider the problem of localizing multiple sources based on noisy distance measurements between the sources and the sensors, in which the source-measurement association is unknown. We develop a mixed-integer conic relaxation of the problem and propose a second-order cone-based outer approximation algorithm for solving it. We show that the proposed algorithm enjoys finite convergence and present numerical results to demonstrate its viability.
Joint work with Sherry Ni and K-F Cheung.

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