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Multichannel Sampling with Unknown Gains and Offsets: A Fast Reconstruction Algorithm

Related publications (76)

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Practical considerations for in vivo MRI with higher dimensional spatial encoding

Daniel Gallichan

This work seeks to examine practical aspects of in vivo imaging when spatial encoding is performed with three or more encoding channels for a 2D image. The recently developed 4-Dimensional Radial In/Out (4D-RIO) trajectory is compared in simulations to an ...

Springer-Verlag2012

A Background Calibration Method for DAC Mismatch Correction in Multibit Sigma-Delta Modulators

Pierre-André Farine, Steve Tanner, Shafqat Ali

A topology for the calibration of DAC errors in multi-bit sigma delta modulators is presented. The proposed technique enables the calibration to proceed in the background. In this technique, two DACs are used in a time-interleaved fashion. One DAC is calib ...

2012

Diffractionless Fourier Domain Microscopy

Theo Lasser, Rainer Leitgeb, Cédric Blatter, Tilman Schmoll

Several methods have been proposed and realized to increase the lateral resolution in microscopy and ultimately to beat the actual diffraction limit as stated by Abbe. Structured illumination for example enhances the lateral resolution by virtually extendi ...

2011

A novel sampling theorem on the sphere

Yves Wiaux, Jason Douglas McEwen

We develop a novel sampling theorem on the sphere and corresponding fast algorithms by associating the sphere with the torus through a periodic extension. The fundamental property of any sampling theorem is the number of samples required to represent a ban ...

Institute of Electrical and Electronics Engineers2011

3D Near-Infrared Imaging Based on a Single-Photon Avalanche Diode Array Sensor

Matthias Wolf, Edoardo Charbon, Juan Mata Pavia

An imager for optical tomography was designed based on a detector with 128x128 single-photon pixels that included a bank of 32 time-to-digital converters. Due to the high spatial resolution and the possibility of performing time resolved measurements, a ne ...

2011

Random Sampling ADC for Sparse Spectrum Sensing

Andreas Peter Burg

Scanning large bandwidths (spectrum sensing) pushes today’s analog hardware to its limits since periodic sampling at Nyquist rate with sufficient resolution is often prohibitively complex. In this paper, we consider a scenario where the signal to be acquir ...

2011

Continuous-Time AR Model Identification: Does Sampling Rate Really Matter?

Michaël Unser, Hagay Kirshner, Simona Maggio

We address the problem of identifying continuous-time auto regressive (CAR) models from sampled data. The exponential nature of CAR autocorrelation functions is taken into account by means of exponential B-splines modelling, allowing one to associate the a ...

EURASIP2010

Signal Processing in Space and Time

Francisco Pereira Correia Pinto

Sound waves propagate through space and time by transference of energy between the particles in the medium, which vibrate according to the oscillation patterns of the waves. These vibrations can be captured by a microphone and translated into a digital sig ...

EPFL2010

Learning Sparse Systems at Sub-Nyquist Rates: A Frequency-Domain Approach

Martin Vetterli, Yue Lu

We propose a novel algorithm for sparse system identification in the frequency domain. Key to our result is the observation that the Fourier transform of the sparse impulse response is a simple sum of complex exponentials, whose parameters can be efficient ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Sensing and Recovery under Sparsity Constraints

Ali Hormati

Popular transforms, like the discrete cosine transform or the wavelet transform, owe their success to the fact that they promote sparsity. These transforms are capable of extracting the structure of a large class of signals and representing them by a few t ...

EPFL2010