Model-based compressive sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for the acquisition
of sparse or compressible signals that can be well approximated by just K¿ N elements from …
of sparse or compressible signals that can be well approximated by just K¿ N elements from …
[PDF][PDF] Proximal methods for hierarchical sparse coding
Sparse coding consists in representing signals as sparse linear combinations of atoms
selected from a dictionary. We consider an extension of this framework where the atoms are …
selected from a dictionary. We consider an extension of this framework where the atoms are …
Exploiting prior knowledge in compressed sensing wireless ECG systems
LF Polania, RE Carrillo… - IEEE journal of …, 2014 - ieeexplore.ieee.org
Recent results in telecardiology show that compressed sensing (CS) is a promising tool to
lower energy consumption in wireless body area networks for electrocardiogram (ECG) …
lower energy consumption in wireless body area networks for electrocardiogram (ECG) …
[图书][B] Time-frequency and time-scale methods: adaptive decompositions, uncertainty principles, and sampling
Developed in this book are several deep connections between time-frequency
(Fourier/Gabor) analysis and time-scale (wavelet) analysis, emphasizing the powerful …
(Fourier/Gabor) analysis and time-scale (wavelet) analysis, emphasizing the powerful …
Exploiting the wavelet structure in compressed sensing MRI
Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space
sampling. According to structured sparsity theories, fewer measurements are required for …
sampling. According to structured sparsity theories, fewer measurements are required for …
Compressed sensing MRI via two-stage reconstruction
Compressed sensing (CS) has been applied to magnetic resonance imaging for the
acceleration of data collection. However, existing CS techniques usually produce images …
acceleration of data collection. However, existing CS techniques usually produce images …
Beyond Besov spaces, part 2: oscillation spaces
S Jaffard - Constructive approximation, 2004 - Springer
We study several extensions of Besov spaces; these extensions include the oscillation
spaces O ps, s' which take into account correlations between the positions of large wavelet …
spaces O ps, s' which take into account correlations between the positions of large wavelet …
[HTML][HTML] On the Besov regularity of periodic Lévy noises
In this paper, we study the Besov regularity of Lévy white noises on the d-dimensional torus.
Due to their rough sample paths, the white noises that we consider are defined as …
Due to their rough sample paths, the white noises that we consider are defined as …
High‐frequency subband compressed sensing MRI using quadruplet sampling
K Sung, BA Hargreaves - Magnetic resonance in medicine, 2013 - Wiley Online Library
Purpose To present and validate a new method that formalizes a direct link between k‐
space and wavelet domains to apply separate undersampling and reconstruction for high …
space and wavelet domains to apply separate undersampling and reconstruction for high …
Applied and Numerical Harmonic Analysis
JJ Benedetto - (No Title), 2007 - Springer
Frame theory is nowadays a fundamental research area in mathematics, computer science,
and engineering with many exciting applications in a variety of different fields. Introduced in …
and engineering with many exciting applications in a variety of different fields. Introduced in …