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Novel Algorithms on Impulse Radio Ultra-WideBand Ranging

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Bilinear Generalized Approximate Message Passing—Part II: Applications

Volkan Cevher

In this paper, we extend the generalized approximate message passing (G-AMP) approach, originally proposed for high-dimensional generalized-linear regression in the context of compressive sensing, to the generalized-bilinear case. In Part I of this two-par ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Lorentzian Iterative Hard Thresholding: Robust Compressed Sensing With Prior Information

Rafael Eduardo Carrillo Rangel

Commonly employed reconstruction algorithms in compressed sensing (CS) use the L-2 norm as the metric for the residual error. However, it is well-known that least squares (LS) based estimators are highly sensitive to outliers present in the measurement vec ...

Institute of Electrical and Electronics Engineers2013

ABC Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis

This paper introduces a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The main advantage is that we only require a prior distribution on a class of simulators (generative mode ...

2013

Bayesian Estimation for Continuous-Time Sparse Stochastic Processes

Michaël Unser, Arash Amini, Emrah Bostan, Ulugbek Kamilov

We consider continuous-time sparse stochastic processes from which we have only a finite number of noisy/noiseless samples. Our goal is to estimate the noiseless samples (denoising) and the signal in-between (interpolation problem). By relying on tools fro ...

Ieee-Inst Electrical Electronics Engineers Inc2013

A Euclidean Likelihood Estimator for Bivariate Tail Dependence

Michal Warchol, Boris Oumow

The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain moment condition. We propose a Euclidean likelihood-based estimator for the ...

Taylor & Francis Inc2013

Online Model Estimation of Ultra-Wideband TDOA Measurements for Mobile Robot Localization

Alcherio Martinoli, Amanda Stella Markowska Prorok

Ultra-wideband (UWB) localization is a recent technology that promises to outperform many indoor localization methods currently available. Yet, non-line-of-sight (NLOS) positioning scenarios can create large biases in the time-difference-of-arrival (TDOA) ...

Ieee2012

Posterior Features for Template-based ASR

Hervé Bourlard, Joel Praveen Pinto, Serena Soldo

This paper investigates the use of phoneme class conditional probabilities as features (posterior features) for template-based ASR. Using 75 words and 600 words task-independent and speaker-independent setup on Phonebook database, we investigate the use of ...

2011

Experimental charge density of LiBD4 from maximum entropy method

Philippe Mauron

We report on maximum entropy method study of the experimental atomic and ionic charges of LiBD4 in its low-temperature orthorhombic phase. Synchrotron radiation x-ray powder diffraction data, neutron powder diffraction data, and density functional calculat ...

2011

Learning in Gaussian Markov random fields

Thomas Riedl

This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown parameter. Thus in order to support the state estimator with prior information o ...

2010

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