18 citations · 18 across the 9 of their papers we have counts for
5 papers · 1 filter
Lifted Restricted Isometry Property and Fast Algorithm for Spectral Compressed Sensing With Near-Optimal Sample Complexity
Xunmeng Wu, Jian-Feng Cai, Zongben Xu +1
This paper studies the spectral compressed sensing problem, which aims to recover an -spectrally-sparse signal of length from linear compressive measurements. We reformulate…
Jointly Sparse Blind Deconvolution via Riemannian Optimization
Wenlong Wang, Baiyang Guo, Zai Yang +2
Blind deconvolution has been widely applied in system identification and signal processing. While joint sparsity commonly arises in practical scenarios, effectively exploiting this…
Quotient Manifold Optimization for Spectral Compressed Sensing
Wenlong Wang, Wen Huang, Zai Yang
Spectral compressed sensing involves reconstructing a spectral-sparse signal from a subset of uniformly spaced samples, with applications in radar imaging and wireless channel esti…
Low-Complexity Algorithms for Multichannel Spectral Super-Resolution
Xunmeng Wu, Zai Yang, Zongben Xu
This paper studies the problem of multichannel spectral super-resolution with either constant amplitude (CA) or not. We propose two optimization problems based on low-rank Hankel-T…
Multichannel Frequency Estimation with Constant Amplitude via Convex Structured Low-Rank Approximation
Xunmeng Wu, Zai Yang, Zongben Xu
We study the problem of estimating the frequencies of several complex sinusoids with constant amplitude (CA) (also called constant modulus) from multichannel signals of their super…