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Reduced-Dimension Linear Transform Coding of Correlated Signals in Networks

Publications associées (87)

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One-Bit Measurements With Adaptive Thresholds

Michaël Unser, Arash Amini, Ulugbek Kamilov, Aurélien Bourquard

We introduce a new method for adaptive one-bit quantization of linearmeasurements and propose an algorithm for the recovery of signals based on generalized approximate message passing (GAMP). Our method exploits the prior statistical information on the sig ...

Ieee-Inst Electrical Electronics Engineers Inc2012

On multicasting nested message sets over combination networks

Suhas Diggavi, Vinod Malathidevi Prabhakaran, Shirin Saeedi Bidokhti

In this paper, we study delivery of two nested message sets over combination networks with an arbitrary number of receivers, where a subset of receivers (public receivers) demand only the lower priority message and a subset of receivers (private receivers) ...

Ieee2012

LP Residual Features for Robust, Privacy-Sensitive Speaker Diarization

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

We present a comprehensive study of linear prediction residual for speaker diarization on single and multiple distant microphone conditions in privacy-sensitive settings, a requirement to analyze a wide range of spontaneous conversations. Two representatio ...

Idiap2011

LP Residual Features for Robust, Privacy-Sensitive Speaker Diarization

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

2011

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

Sparse Image Representation by Directionlets

Martin Vetterli, Vladan Velisavljevic, Pier Luigi Dragotti

Despite the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency and sparsity of its representation are limited by the spatial symmetry and separability of its basis functions built in the horizontal and vertic ...

Elsevier2010

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

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

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

A Greedy Approach To The Distributed Karhunen-Loeve Transform

Michael Christoph Gastpar

In the distributed linear source coding problem a set of distributed sensors observe subsets of a data vector, and provide the fusion center with linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion center ...

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