Publications related to Signal

Learning-Based Compressive Subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The problem of recovering a structured signal

\mathbf{x} \in \mathbb{C}^p

from a set of dimensionality-reduced linear measurements

\mathbf{b} = \mathbf {A}\mathbf {x}

arises in a variety of applications, such as medical imaging, spectroscopy, Fourier o ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Principles of Systems Biology, No. 11

Vassily Hatzimanikatis, Jasmin Maria Hafner, Noushin Hadadi, Laurent Potvin-Trottier

This month: AI that learns patterns and facts, new protein-RNA and protein-protein relationships, engineering signaling and metabolism, and more variants of Cas9. ...

Cell Press2016

Learning Data Triage: Linear Decoding Works for Compressive MRI

Volkan Cevher, Yen-Huan Li

The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery algorithm based on the known structure. This approach requires looking for ...

Ieee2016

Signal-Adapted Tight Frames on Graphs

Dimitri Nestor Alice Van De Ville, Hamid Behjat

The analysis of signals on complex topologies modeled by graphs is a topic of increasing importance. Decompositions play a crucial role in the representation and processing of such information. Here, we propose a new tight frame design that is adapted to a ...

Institute of Electrical and Electronics Engineers2016

"Can you hear me now?"

Raphaël Marc Ullmann

This thesis deals with signal-based methods that predict how listeners perceive speech quality in telecommunications. Such tools, called objective quality measures, are of great interest in the telecommunications industry to evaluate how new or deployed sy ...

EPFL2016

Methods and systems for skew tolerance in and advanced detectors for vector signaling codes for chip-to-chip communication

Mohammad Amin Shokrollahi, Anant Pratap Singh

Advanced detectors for vector signaling codes are disclosed which utilize multi-input comparators, generalized on-level slicing, reference generation based on maximum swing, and reference generation based on recent values. Vector signaling codes communicat ...

2016

Audio inpainting with similarity graphs

Nathanaël Perraudin

In this contribution, we present a method to compensate for long duration data gaps in audio signals, in particular music. To achieve this task, a similarity graph is constructed, based on a short-time Fourier analysis of reliable signal segments, e.g. the ...

2016

Efficient processing and detection of balanced codes

Mohammad Amin Shokrollahi

Circuits that are matched to balanced codes may recover transmitted information in a noise resilient and power efficient manner. Circuit components for processing a balanced code may include one or more of: matched amplification of the signals representing ...

2016

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Volkan Cevher

We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. O ...

Institute of Electrical and Electronics Engineers2016

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Ambrogio Fasoli, Duccio Testa, Patrick Blanchard, Jonathan Bryan Lister, Theodoros Panis, Mattia Albergante

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which two examples are the JET and ITER tokamaks. One problem which is common to these fields is t ...

IOP2016

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Learning-Based Compressive Subsampling

Principles of Systems Biology, No. 11

Learning Data Triage: Linear Decoding Works for Compressive MRI

Signal-Adapted Tight Frames on Graphs

"Can you hear me now?"

Methods and systems for skew tolerance in and advanced detectors for vector signaling codes for chip-to-chip communication

Audio inpainting with similarity graphs

Efficient processing and detection of balanced codes

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

"Can you hear me now?"

Learning-Based Compressive Subsampling

Signal-Adapted Tight Frames on Graphs

Audio inpainting with similarity graphs

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Efficient processing and detection of balanced codes

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Principles of Systems Biology, No. 11

Learning Data Triage: Linear Decoding Works for Compressive MRI

Methods and systems for skew tolerance in and advanced detectors for vector signaling codes for chip-to-chip communication