65 citations · 128 across the 11 of their papers we have counts for
6 papers · 1 filter
Fast Reconstruction of High-qubit Quantum States via Low Rate Measurements
K. Li, J. Zhang, S. Cong
Due to the exponential complexity of the resources required by quantum state tomography (QST), people are interested in approaches towards identifying quantum states which require…
State of the Art and Prospects of Structured Sensing Matrices in Compressed Sensing
Kezhi Li, Shuang Cong
Compressed sensing (CS) enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampling rate is much low…
Piecewise Toeplitz Matrices-based Sensing for Rank Minimization
Kezhi Li, Cristian R. Rojas, Saikat Chatterjee +1
This paper proposes a set of piecewise Toeplitz matrices as the linear mapping/sensing operator for recovering l…
A Robust Compressive Quantum State Tomography Algorithm Using ADMM
Kezhi Li, Shuang Cong
The possible state space dimension increases exponentially with respect to the number of qubits. This feature makes the quantum state tomography expensive and impractical for ident…
Convolutional Compressed Sensing Using Deterministic Sequences
Kezhi Li, Lu Gan, Cong Ling
In this paper, a new class of circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, th…
Orthogonal symmetric Toeplitz matrices for compressed sensing: Statistical isometry property
Kezhi Li, Lu Gan, Cong Ling
Recently, the statistical restricted isometry property (RIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this paper…