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Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime

Related publications (61)

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Robust Array Calibration Using Time Delays with Application to Ultrasound Tomography

Martin Vetterli, Olivier Roy, Ivana Jovanovic

Accurate calibration is a requirement of many array signal processing techniques. We investigate the calibration of a transducer array using time delays. We derive a strategy based on the mean square error criterion and discuss how time delays that are not ...

2011

Moving horizon estimation for distributed nonlinear systems with application to cascade river reaches

Giancarlo Ferrari Trecate, Marcello Farina

In this paper we consider a nonlinear constrained system observed by a sensor network and propose a distributed state estimation scheme based on moving horizon estimation (MHE). In order to embrace the case where the whole system state cannot be reconstruc ...

2011

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

Ali H. Sayed

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton's method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of l ...

IEEE2010

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

Unbiased Model Combinations for Adaptive Filtering

Ali H. Sayed

In this paper, we consider model combination methods for adaptive filtering that perform unbiased estimation. In this widely studied framework, two adaptive filters are run in parallel, each producing unbiased estimates of an underlying linear model. The o ...

IEEE2010

Frame Domain Signal Processing: Framework and Applications

Martin Vetterli, Amina Chebira

Besides basis expansions, frames representations play a key role in signal processing. We thus consider the problem of frame domain signal processing, which is more complex and challenging than transform domain processing. Examples of such processing aboun ...

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

Undecimated Haar Thresholding For Poisson Intensity Estimation

Michaël Unser, Thierry Blu, Florian Luisier

We propose a novel algorithm for denoising Poisson-corrupted images, that performs a signal-adaptive thresholding of the undecimated Haar wavelet coefficients. A Poisson's unbiased MSE estimate is devised and adapted to arbitrary transform-domain pointwise ...

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

Undecimated Haar Thresholding for Poisson Intensity Estimation

Michaël Unser, Thierry Blu, Florian Luisier

IEEE2010

Public space in Beijing

Béatrice Ferrari

This is a short exploration of public space in Beijing (and elsewhere). But how do we define public space and does it exist as such in Beijing? In this short presentation, instead of simply focusing on physical spaces, I will try to capture some of the ele ...

2010

Distributed moving horizon estimation for nonlinear constrained systems

Giancarlo Ferrari Trecate, Marcello Farina

In this paper we consider a nonlinear constrained system observed by a sensor network and propose a distributed state estimation scheme based on Moving Horizon Estimation (MHE). In order to embrace the case where the whole system state cannot be reconstruc ...

2010