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Spatio-Temporal Diffusion Strategies for Estimation and Detection Over Networks

Publications associées (48)

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MMSE Denoising of Sparse and Non-Gaussian AR(1) Processes

Michaël Unser, Emrah Bostan, Pedram Pad, Pouria Tohidi

We propose two minimum-mean-square-error (MMSE) estimation methods for denoising non-Gaussian first-order autoregressive (AR(1)) processes. The first one is based on the message passing framework and gives the exact theoretic MMSE estimator. The second is ...

IEEE2016

Fast Estimation of Plant Steady State, with Application to Static RTO

Dominique Bonvin, Julien Léo Billeter, Michael Amrhein, Diogo Filipe Mateus Rodrigues

Experimental assessment or prediction of plant steady state is important for many applications in the area of modeling and operation of continuous processes. For example, the iterative implementation of static real-time optimization requires reaching stead ...

2016

Blood flow velocity field estimation via spatial regression with PDE penalization

Fabio Nobile

We propose an innovative method for the accurate estimation of surfaces and spatial fields when prior knowledge of the phenomenon under study is available. The prior knowledge included in the model derives from physics, physiology, or mechanics of the prob ...

American Statistical Association2015

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In this paper, a case study on the estimations of extreme floods is described. The watershed chosen for the analysis is the catchment of the Limmernboden dam situated in Switzerland. Statistical methods and the simulation based "Probable Maximum Precipitat ...

Copernicus Gesellschaft Mbh2015

Estimation of Space-Time Varying Parameters Using a Diffusion LMS Algorithm

Ali H. Sayed

We study the problem of distributed adaptive estimation over networks where nodes cooperate to estimate physical parameters that can vary over both space and time domains. We use a set of basis functions to characterize the space-varying nature of the para ...

2014

In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...

EPFL2014

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Scientists in many disciplines have progressively been using simulations to better understand the natural systems they study. Faster hardware, as well as increasingly precise instruments, allow the construction and simulation of progressively advanced mod ...

2014

Outlier removal for improved source estimation in atmospheric inverse problems

Martin Vetterli, Marta Martinez-Camara

Estimation of the quantities of harmful substances emitted into the atmosphere is one of the main challenges in modern environmen- tal sciences. In most of the cases, this estimation requires solving a linear inverse problem. A key difficulty in evaluating ...

Ieee2014

Scale preserving PTZ tracking with size estimation using tilt sensory data

Kwang Moo Yi

We propose an pan-tilt-zoom (PTZ) tracking method to keep the target object at the center of the image with a predefined size in image. For this purpose, we develop an efficient method for object size estimation using only the tilt sensory data. First we i ...

2014

MMSE Estimation of Sparse Levy Processes

Michaël Unser, Arash Amini, Ulugbek Kamilov, Pedram Pad

We investigate a stochastic signal-processing framework for signals with sparse derivatives, where the samples of a Levy process are corrupted by noise. The proposed signal model covers the well-known Brownian motion and piecewise-constant Poisson process; ...

Ieee-Inst Electrical Electronics Engineers Inc2013