Title: Sparse Methods in Array Imaging
Speaker: İlker Koçyiğit, Dept. of Mathematics - University of Michigan, Ann Arbor
Date/Time: Friday, May 27, 10:40-11:30
Place: FENS G035
In array imaging the goal is to recover an unknown source (or scatterer) configuration from measurements of the wave field at the sensor array. Various ideas from compressive sensing have been applied to array imaging problems. In this talk we discuss some of these sparsity promoting methods and the issues that arise in their application. We discuss the stability and resolution of reconstructed images and how they are related to the features of the source configuration, in particular sparsity and well-separatedness properties of the support of the unknown configuration. We present numerical simulations to support these theoretical results..
Bio: İlker Koçyiğit received Ph.D. degree in Mathematics from University of Washington, Seattle in 2013. Since then he is a postdoctoral Assistant Professor at University of Michigan, Ann Arbor in department of Mathematics. His research interests include imaging, inverse problems and interactions of them with signal processing. Previously he worked in software industry. He has a BSc in Computer Engineering from METU and MSc in Mathematical Engineering from İTÜ. After receiving his B.Sc. degree he worked on various software development projects. He is a co-founder of RiskTurk, an İstanbul based company developing risk management solutions using tools from financial mathematics.
Contact: Müjdat Çetin