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The regularized tau estimator: A robust and efficient solution to ill-posed linear inverse problems

Publications associées (99)

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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

Speech Enhancement using an Improved MMSE Estimator with Laplacian Prior

In this paper we present an optimal estimator of magnitude spectrum for speech enhancement when the clean speech DFT coefficients are modeled by a Laplacian distribution and the noise DFT coefficients are modeled by a Gaussian distribution. Chen has alread ...

2010

A Simplified Estimation Scheme for the Number of Vehicles in Signalized Links

The number of vehicles that are included in a metered motorway ramp or an urban signalized link at any time is valuable information for real-time control. A recently developed Kalman-filter-based real-time estimator for the vehicle count within signalized ...

Institute of Electrical and Electronics Engineers2010

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

Distributed moving horizon estimation for nonlinear constrained systems

Giancarlo Ferrari Trecate, Marcello Farina

2010

Robust inference for generalized linear models

Sahar Hosseinian Ehrensberger

Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...

EPFL2009

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

Distributed Karhunen-Loeve Transform With Nested Subspaces

Michael Christoph Gastpar, Naveen Goela

A network in which sensors observe a common Gaussian source is analyzed. Using a fixed linear transform, each sensor compresses its high-dimensional observation into a low-dimensional representation. The latter is provided to a central decoder that reconst ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Impulse Radio Ultra-WideBand ranging and localization for sensor networks

Hai Zhan

In this thesis, we focus on Impulse Radio (IR) Ultra-WideBand (UWB) ranging and positioning techniques under indoor propagation environments. IR-UWB, a new carrierless communication scheme using impulses, is a candidate technology for future communication, ...

EPFL2009

Linear Compressive Networks

Michael Christoph Gastpar, Naveen Goela

A linear compressive network (LCN) is defined as a graph of sensors in which each encoding sensor compresses incoming jointly Gaussian random signals and transmits (potentially) low-dimensional linear projections to neighbors over a noisy uncoded channel. ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009