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Low Complexity Iterative Signal Processing Methods

 

Project staff
Dr. Michael Lunglmayr


Project description
The goal of this project is to develop low complexity iterative signal processing methods, mainly for estimation. The focus lies on developing low complexity algorithms suited for hardware implementation, as well as formulating the theoretical framework behind them. (FoDok)


Publications

4) Lunglmayr M., Huemer M.: Efficient Linearized Bregman Iteration for Sparse Adaptive Filters and Kaczmarz Solvers, in: IEEE (Eds.): Proceedings of IEEE 9th Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), 2016.

3) Lunglmayr M., Huemer M.: "Parameter Optimization for Step-Adaptive Approximate Least Squares", in: Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015, Volume 9520, Page(s) 521-528, Springer International Publishing, 2015, Link

2) Lunglmayr M., Unterrieder C., Huemer M.: "Step-adaptive Approximate Least Squares", in: Proceedings of the 23rd European Signal Processing Conference (EUSIPCO 2015), Page(s) 1113-1117, 2015.

1) Lunglmayr M., Unterrieder C., Huemer M.: "Approximate Least Squares", in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Page(s) 4711-4715, 2014.