Publications related to A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Bound and Conquer: Improving Triangulation by Enforcing Consistency

Martin Vetterli, Adam James Scholefield, Alireza Ghasemi

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction error decays quadratically as more cameras are added to the system. Furtherm ...

2019

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Juri Ranieri, Gilles Baechler, Amina Chebira, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

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

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Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Decoder Partitioning: Towards Practical List Decoding of Polar Codes

Rüdiger Urbanke, Seyed Hamed Hassani, Marco Mondelli

Polar codes represent one of the major recent breakthroughs in coding theory and, because of their attractive features, they have been selected for the incoming SG standard. As such, a lot of attention has been devoted to the development of decoding algori ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Near-Optimal Noisy Group Testing via Separate Decoding of Items

Volkan Cevher, Jonathan Mark Scarlett

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of tests, and is relevant in applications such as medical testing, communication protocols, pattern matching, and more. In this pa ...

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

Martin Vetterli, Benjamin Bejar Haro

We address the problem of sampling and reconstruction of sparse signals with finite rate of innovation. We derive general conditions under which perfect reconstruction is possible for sampling kernels satisfying Strang-Fix conditions. Previous results on t ...

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

Nicolas Macris, Jean François Emmanuel Barbier, Chun Lam Chan

A new adaptive path interpolation method has been recently developed as a simple and versatile scheme to calculate exactly the asymptotic mutual information of Bayesian inference problems defined on dense factor graphs. These include random linear and gene ...

IEEE2018

Rake, Peel, Sketch

Robin Scheibler

The prototypical signal processing pipeline can be divided into four blocks. Representation of the signal in a basis suitable for processing. Enhancement of the meaningful part of the signal and noise reduction. Estimation of important statistical properti ...

EPFL2017

Coding for Communications and Secrecy

Mani Bastaniparizi

Shannon, in his landmark 1948 paper, developed a framework for characterizing the fundamental limits of information transmission. Among other results, he showed that reliable communication over a channel is possible at any rate below its capacity. In 2008, ...

EPFL2017

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

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

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Bound and Conquer: Improving Triangulation by Enforcing Consistency

Super Resolution Phase Retrieval for Sparse Signals

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

Decoder Partitioning: Towards Practical List Decoding of Polar Codes

Near-Optimal Noisy Group Testing via Separate Decoding of Items

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

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

Rake, Peel, Sketch

Coding for Communications and Secrecy

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Super Resolution Phase Retrieval for Sparse Signals

Bound and Conquer: Improving Triangulation by Enforcing Consistency

Decoder Partitioning: Towards Practical List Decoding of Polar Codes

Near-Optimal Noisy Group Testing via Separate Decoding of Items

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

Rake, Peel, Sketch

Coding for Communications and Secrecy

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

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

An Adaptive Sublinear-Time Block Sparse Fourier Transform