Concept

Autocovariance

Publications associées (34)

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Estimating intensity fields of stochastic phenomenons is of crucial interest in many scientific applications. Typical experimental setups involve an acquisition system, that subsequently filters and samples the probed intensity field. This equivalently def ...

2016

Optical coherence correlation spectroscopy (OCCS)

Theo Lasser, Christophe Pache, Marcel Leutenegger, Arno Pino Bouwens, Stefan Geissbühler, Akihiro Sato, Stéphane Broillet

We present a new method called optical coherence correlation spectroscopy (OCCS) using nanoparticles as reporters of kinetic processes at the single particle level. OCCS is a spectral interferometry based method, thus giving simultaneous access to several ...

Optical Society of America2014

Fourier Analysis of Functional Time Series, with Applications to DNA Dynamics

Shahin Tavakoli

This work is about time series of functional data (functional time series), and consists of three main parts. In the first part (Chapter 2), we develop a doubly spectral decomposition for functional time series that generalizes the Karhunen–Loève expansion ...

EPFL2014

Length scales and self-organization in dense suspension flows

Matthieu Wyart

Dense non-Brownian suspension flows of hard particles display mystifying properties: As the jamming threshold is approached, the viscosity diverges, as well as a length scale that can be identified from velocity correlations. To unravel the microscopic mec ...

2014

Probabilistic assessment of the process-noise covariance matrix of discrete Kalman filter state estimation of active distribution networks

Mario Paolone, Marco Pignati, Lorenzo Zanni, Styliani Sarri

The accuracy of state estimators using the Kalman Filter (KF) is largely influenced by the measurement and the process noise covariance matrices. The former can be directly inferred from the available measurement devices whilst the latter needs to be asses ...

IEEE2014

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Michaël Unser, John Paul Ward, Aurélien Bourquard, Hagay Kirshner

We introduce an adaptive continuous-domain modeling approach to texture and natural images. The continuous-domain image is assumed to be a smooth function, and we embed it in a parameterized Sobolev space. We point out a link between Sobolev spaces and sto ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Optical Coherence Correlation Spectroscopy

Stéphane Broillet

Questions such as biomolecular interactions, kinetics of enzymes, DNA conformational changes, cellular structures properties (among others) are addressed by characterizing the biological function of molecules. This function depends on their structure and t ...

EPFL2014

Direct observation of the full transition from ballistic to diffusive Brownian motion in a liquid

Sylvia Jeney, Branimir Lukic

At timescales once deemed immeasurably small by Einstein, the random movement of Brownian particles in a liquid is expected to be replaced by ballistic motion. So far, an experimental verification of this prediction has been out of reach due to a lack of i ...

2011

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Andreas Krause, Matthias Seeger

Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve ...

Omnipress2010

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Andreas Krause, Matthias Seeger

Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multi-armed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve ...

2010

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