Publications associées à Unified Theory for Recovery of Sparse Signals in a General Transform Domain

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An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Unified Theory for Recovery of Sparse Signals in a General Transform Domain

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Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

Learning of robust spectral graph dictionaries for distributed processing

Compressive Multiplexing of Ultrasound Signals

Compressive Multiplexing of Ultrasound Signals

Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Sparse inverse problems for Fourier imaging

Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

Compressive Multiplexing of Ultrasound Signals

Compressive Multiplexing of Ultrasound Signals

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Sparse inverse problems for Fourier imaging

Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model

Learning of robust spectral graph dictionaries for distributed processing

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation