Concept

Stationary process

Related publications (133)

Application of Time Series Methods on Long-Term Structural Monitoring Data for Fatigue Analysis

Eugen Brühwiler, Bartlomiej Wojciech Sawicki, Morteza Ahmadivala

Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...

2019

The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications

Daniel Kuhn, Wolfram Wiesemann

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naively partition or discretize the support of the random problem parameters are limited to sma ...

2019

The asymmetric multitype contact process

Thomas Mountford, Daniel Rodrigues Valesin

We study the multitype contact process on Z(d) under the assumption that one of the types has a birth rate that is larger than that of the other type, and larger than the critical value of the standard contact process. We prove that, if initially present, ...

ELSEVIER SCIENCE BV2019

A Physical Model of Non-stationary Blur in Ultrasound Imaging

Jean-Philippe Thiran, Yves Wiaux, Paul Hurley, Dimitris Perdios, Matthieu Martin Jean-André Simeoni, Marcel Arditi, Adrien Georges Jean Besson

Conventional ultrasound (US) imaging relies on delay-and-sum (DAS) beamforming which retrieves a radio- frequency (RF) image, a blurred estimate of the tissue reflectivity function (TRF). Despite the non-stationarity of the blur induced by propagation effe ...

2018

Reduced Leakage Synchrophasor Estimation: Hilbert Transform Plus Interpolated DFT

Mario Paolone, Asja Derviskadic, Guglielmo Frigo

Synchrophasor estimation is typically performed by means of spectral analysis based on the discrete Fourier transform (DFT). Traditional DFT approaches, though, suffer from several uncertainty contributions due to the stationarity assumption, spectral leak ...

2018

Stationary signal processing on graphs

Pierre Vandergheynst, Nathanaël Perraudin

Graphs are a central tool in machine learning and information processing as they allow to conveniently capture the structure of complex datasets. In this context, it is of high importance to develop flexible models of signals defined over graphs or network ...

Institute of Electrical and Electronics Engineers2017

Gaussian versus Sparse Stochastic Processes

Julien René Pierre Fageot

Although our work lies in the field of random processes, this thesis was originally motivated by signal processing applications, mainly the stochastic modeling of sparse signals. We develop a mathematical study of the innovation model, under which a signal ...

EPFL2017

Generalized Pickands constants and stationary max-stable processes

Sebastian Engelke

Pickands constants play a crucial role in the asymptotic theory of Gaussian processes. They are commonly defined as the limits of a sequence of expectations involving fractional Brownian motions and, as such, their exact value is often unknown. Recently, D ...

Springer Verlag2017

On the Besov regularity of periodic Levy noises

Michaël Unser, Julien René Pierre Fageot, John Paul Ward

In this paper, we study the Besov regularity of Levy white noises on the d-dimensional torus. Due to their rough sample paths, the white noises that we consider are defined as generalized stochastic fields. We, initially, obtain regularity results for gene ...

Academic Press Inc Elsevier Science2017

AUTOREGRESSIVE MOVING AVERAGE GRAPH FILTERS A STABLE DISTRIBUTED IMPLEMENTATION

Andreas Loukas

We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come ...

Ieee2017

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