Publications related to Sampling signals with finite rate of innovation: the noisy case

Bolometric detection of ferromagnetic resonance in YIG slab

Jean-Philippe Ansermet, Haiming Yu, Sa Tu, Marcin Bialek, Yao Zhang

The resistance of the Pt bar deposited on the YIG slab was monitored while the magnetic field was ramped through the ferromagnetic resonance with the YIG slab facing a coplanar waveguide resonator excited at 4.3 GHz excitation. The resistance change provid ...

Elsevier2017

How does one compute the noise power to simulate real and complex GNSS signals?

Cyril Botteron, Jérôme Leclère

Simulation of GNSS signals is very important to test and validate algorithms. With some algorithms, such as acquisition or tracking, we do not need to simulate a realistic constellation with actual ranges, Doppler or navigation data. We can simply simulate ...

2016

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Spatial fringe analysis techniques for multiple phase and phase derivative estimation

Rishikesh Dilip Kulkarni

Analysis of fringe patterns for the accurate estimation of phase and phase derivatives is of crucial importance in optical interferometry as these quantities provide important information on the physical parameters under study. A wide range of applications ...

EPFL2016

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Adrien Georges Jean Besson, Olivier Bernard

The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with prom ...

Ieee2016

CORRELATED MULTIPLE SAMPLING CMOS IMAGE SENSOR

Assim Boukhayma

A CMOS image sensor including at least one pixel and one circuit arranged to receive, on a first node of the circuit, an analog signal representative of the luminosity level received by the pixel, the circuit being capable of successively acquiring 2n samp ...

2016

Evaluation of the accuracy of BOTDA systems based on the phase spectral response

Luc Thévenaz, Marcelo Alfonso Soto Hernandez, Alejandro Dominguez Lopez

We evaluate the Brillouin frequency shift (BFS) determination error when utilizing the Brillouin phase spectrum (BPS) instead of the Brillouin gain spectrum (BGS) in BOTDA systems. Systems based on the BPS perform the determination of the BFS through a lin ...

Optical Society of America2016

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

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite-dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

2015

Sampling signals with finite rate of innovation: the noisy case

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Bolometric detection of ferromagnetic resonance in YIG slab

How does one compute the noise power to simulate real and complex GNSS signals?

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Spatial fringe analysis techniques for multiple phase and phase derivative estimation

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

CORRELATED MULTIPLE SAMPLING CMOS IMAGE SENSOR

Evaluation of the accuracy of BOTDA systems based on the phase spectral response

Learning Data Triage: Linear Decoding Works for Compressive MRI

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

CORRELATED MULTIPLE SAMPLING CMOS IMAGE SENSOR

How does one compute the noise power to simulate real and complex GNSS signals?

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Spatial fringe analysis techniques for multiple phase and phase derivative estimation

Evaluation of the accuracy of BOTDA systems based on the phase spectral response

Learning Data Triage: Linear Decoding Works for Compressive MRI

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Bolometric detection of ferromagnetic resonance in YIG slab