Concept

Errors and residuals

Related publications (505)

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Speaker Change Detection with Privacy-Preserving Audio Cues

Hervé Bourlard, Daniel Gatica-Perez, Sree Hari Krishnan Parthasarathi

In this paper we investigate a set of privacy-sensitive audio features for speaker change detection (SCD) in multiparty conversations. These features are based on three different principles: characterizing the excitation source information using linear pre ...

Idiap2009

Estimation of modelling errors in structural system identification

Ian Smith, James-Alexandre Goulet

This paper presents a method for measurement-system design through criteria related to model based structural identification. Using a multi-model approach and results from previous research carried out at EPFL, an improved algorithm is proposed. The algori ...

2009

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

SURE-Based Non-Local Means

Dimitri Nestor Alice Van De Ville, Michel Kocher

Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and difficult to tune. Here, we propose to use Stein's unbiased ...

Institute of Electrical and Electronics Engineers2009

Multivariate calibration of non-replicated measurements for the factored noise model

Nirav Pravinbhai Bhatt

The accuracy of a multivariate calibration (MVC) model for relating concentrations of multicomponent mixtures to their spectral measurements, depends on effective handling of errors in the measured data. For the case when error variances vary along only on ...

2009

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

Predicting User-Cell Association in Cellular Networks from Tracked Data

Jean-Yves Le Boudec

We consider the problem of predicting user location in the form of user-cell association in a cellular wireless network. This is motivated by resource optimization, for example switching base transceiver stations on or off to save on network energy consump ...

Springer Verlag2009

Distributed adaptive learning mechanisms

Ali H. Sayed

The chapter describes recent developments in distributed processing over adaptive networks. The resulting adaptive learning rules rely on local data at the individual nodes and on collaborations among neighboring nodes in order to exploit the space-time di ...

John Wiley & Sons, Inc.2009

Modeling of distortion caused by Markov-model burst packet losses in video transmission

Yi Zhang

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. A Distortion Trellis model is pro- posed, enabling us to estimate at the frame level the expected mean-squ ...

2009

On the representation of droplet coalescence and autoconversion: Evaluation using ambient cloud droplet size distributions

Athanasios Nenes

In this study, we evaluate eight autoconversion parameterizations against integration of the Kinetic Collection Equation (KCE) for cloud size distributions measured during the NASA CRYSTAL-FACE and CSTRIPE campaigns. KCE calculations are done using both th ...

Blackwell Publishing Ltd2009