Concept

Processus stationnaire

Publications associées (133)

Approximate solution of the probability density function of bedload transport rate over multiple time scales.

Christophe Ancey, Joris Heyman, François Mettra, Hongbo Ma

Bedload transport rate in mountain rivers is highly fluctuating and has strong stochastic behavior even under steady flow conditions. Its stochastic description thus offers deeper insights into its dynamics than the deterministic one. As a random quantity, ...

2013

Diffusion Adaptation Over Networks Under Imperfect Information Exchange and Non-Stationary Data

Ali H. Sayed

Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. The combination weights that a ...

IEEE2012

Efficient Schemes for Adaptive Frequency Tracking and their Relevance for EEG and ECG

Jérôme Sébastien Van Zaen

Amplitude and frequency are the two primary features of one-dimensional signals, and thus both are widely utilized to analysis data in numerous fields. While amplitude can be examined directly, frequency requires more elaborate approaches, except in the si ...

EPFL2012

Dominant controls on pesticide transport from tile to catchment scale: Lessons from a minimalist model

Andrea Rinaldo, Gianluca Botter

This paper proposes a minimalist modeling approach for characterizing pesticide concentrations in runoff from agricultural catchments across spatial scales. The model proposed is of an intermediate level of complexity between traditional chromatographic se ...

2012

On the Use of Models for Real-Time Optimization

Dominique Bonvin

The operation of dynamic processes can be optimized using models that predict the system behavior well, in particular its optimality features. In practice, however, process models are often structurally inaccurate, and on-line adaptation is typically requi ...

2012

Bridging the Past, Present and Future: Modeling Scene Activities From Event Relationships and Global Rules

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propose a novel topic model that accounts for the two main factors that affect thes ...

2012

A supervised recalibration protocol for unbiased BCI

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Serafeim Perdikis, Michele Tavella

One important source of performance degradation in BCIs is bias towards one of the mental classes. Recent literature has focused on the general problem of classification accuracy drop, identifying non-stationarity as the generating factor, thus leading to ...

2011

Stochastic Models for Sparse and Piecewise-Smooth Signals

Michaël Unser, Pouya Dehghani Tafti

We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential equations, or, equivalently, in terms of a suitable innovation model; the latter is ana ...

IEEE2011

A procedure based on proper orthogonal decomposition for time-frequency analysis of time series

Giacomo Valerio Iungo

A procedure for time-frequency analysis of time series is described, which is mainly inspired by singular-spectrum analysis, but it presents some modifications that allow checking the convergence of the results and extracting the detected spectral componen ...

Springer Verlag2011

Maximum-Likelihood Identification of Sampled Gaussian Processes

Michaël Unser, Hagay Kirshner, Simona Maggio

This work considers sampled data of continuous-domain Gaussian processes. We derive a maximum-likelihood estimator for identifying autoregressive moving average parameters while incorporating the sampling process into the problem formulation. The proposed ...

SampTA2011

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