58 citations · 97 across the 11 of their papers we have counts for
5 papers · 1 filter
Compressed Sensing of Multi-Channel EEG Signals: The Simultaneous Cosparsity and Low Rank Optimization
Yipeng Liu, Maarten De Vos, Sabine Van Huffel
Goal: This paper deals with the problems that some EEG signals have no good sparse representation and single channel processing is not computationally efficient in compressed sensi…
Simultaneous Greedy Analysis Pursuit for Compressive Sensing of Multi-Channel ECG Signals
Yurrit Avonds, Yipeng Liu, Sabine Van Huffel
This paper addresses compressive sensing for multi-channel ECG. Compared to the traditional sparse signal recovery approach which decomposes the signal into the product of a dictio…
Robust Cosparse Greedy Signal Reconstruction for Compressive Sensing with Multiplicative and Additive Noise
Yurrit Avonds, Yipeng Liu, Sabine Van Huffel
Greedy algorithms are popular in compressive sensing for their high computational efficiency. But the performance of current greedy algorithms can be degenerated seriously by noise…
Multi-Structural Signal Recovery for Biomedical Compressive Sensing
Yipeng Liu, Maarten De Vos, Ivan Gligorijevic +3
Compressive sensing has shown significant promise in biomedical fields. It reconstructs a signal from sub-Nyquist random linear measurements. Classical methods only exploit the spa…
Multi-Sparse Signal Recovery for Compressive Sensing
Yipeng Liu, Ivan Gligorijevic, Vladimir Matic +2
Signal recovery is one of the key techniques of Compressive sensing (CS). It reconstructs the original signal from the linear sub-Nyquist measurements. Classical methods exploit th…