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Differences between observation and sampling error in sparse signal reconstruction

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Clock jitter estimation in noise

Ali H. Sayed

Clock timing jitter refers to random perturbations in the sampling time in analog-to-digital converters (ADCs). The perturbations are caused by circuit imperfections in the sampling clock. This paper analyzes the effect of sampling clock jitter on the acqu ...

IEEE2011

Frequency domain compensation of spurious sidebands in A/D circuits

Ali H. Sayed

In a non-ideal PLL circuit, leakage of the reference signal into the control line produces spurious tones. When the distorted PLL signal is used as a clock signal, it creates spurious tones in the sampled data. Our prior work used a training signal to esti ...

IEEE2011

Sampling Trajectories for Mobile Sensing

Martin Vetterli, Jayakrishnan Unnikrishnan

Classical sampling theory for sampling and reconstructing bandlimited fields in

\Re^d

addresses the problem of sampling on lattice points. We consider a generalization of this problem, in which one samples the field along

1

-dimensional spatial trajecto ...

2011

Sparsity Driven People Localization with a Heterogeneous Network of Cameras

Pierre Vandergheynst, Alexandre Massoud Alahi, Laurent Jacques

In this paper, we propose to study the problem of localization of a dense set of people with a network of heterogeneous cameras. We propose to recast the problem as a linear inverse problem. The proposed framework is generic to any scene, scalable in the n ...

Springer Verlag2011

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

The SURE-LET approach to image denoising

Florian Luisier

Denoising is an essential step prior to any higher-level image-processing tasks such as segmentation or object tracking, because the undesirable corruption by noise is inherent to any physical acquisition device. When the measurements are performed by phot ...

EPFL2010

Model-based compressive sensing

Volkan Cevher

Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K < N elements from an N-dimensional basis. Instead of taking periodic samples, we measure inner ...

Institute of Electrical and Electronics Engineers2010

Spatial Super-Resolution of a Diffusion Field by Temporal Oversampling in Sensor Networks

Martin Vetterli, Yue Lu

We study the spatial-temporal sampling of a linear diffusion field, and show that it is possible to compensate for insufficient spatial sampling densities by oversampling in time. Our work is motivated by the following issue often encountered in sensor net ...

2009

Nonideal sampling and regularized interpolation of noisy data

Sathish Ramani

Conventional sampling (Shannon's sampling formulation and its approximation-theoretic counterparts) and interpolation theories provide effective solutions to the problem of reconstructing a signal from its samples, but they are primarily restricted to the ...

EPFL2009

Sparse Sampling of Signal Innovations

Martin Vetterli, Pina Marziliano, Thierry Blu, Lionel Coulot, Pier Luigi Dragotti

Sparse sampling of continuous-time sparse signals is addressed. In particular, it is shown that sampling at the rate of innovation is possible, in some sense applying Occam's razor to the sampling of sparse signals. The noisy case is analyzed and solved, p ...

Institute of Electrical and Electronics Engineers2008