Publications related to Singular spectrum analysis

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Elevated nitrate from human activity causes ecosystem and economic harm globally. The factors that control the spatiotemporal dynamics of riverine nitrate concentration remain difficult to describe and predict. We analyzed nitrate concentration from 4450 s ...

SPRINGER2023

Covariance Estimation for Random Surfaces beyond Separability

Tomas Masák

This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

EPFL2022

A Novel Approach for Classification and Forecasting of Time Series in Particle Accelerators

Fernando Perez Cruz

The beam interruptions (interlocks) of particle accelerators, despite being necessary safety measures, lead to abrupt operational changes and a substantial loss of beam time. A novel time series classification approach is applied to decrease beam time loss ...

2021

Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability

Eugen Brühwiler

Constructed in 1969, the Chillon viaducts constitute a vital component of the Swiss roadway network. The bridge deck was strengthened in 2015 by means of an Ultra High Performance Fiber Reinforced Cement-based Composite for alleviating the effects of deter ...

2020

Decoding of Self-paced Lower-Limb Movement Intention: A Case Study on the Influence Factors

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Dong Liu

Brain-machine interfaces (BMIs) have been applied as new rehabilitation tools for motor disabled individuals. Active involvement of cerebral activity has been shown to enhance neuroplasticity and thus to restore mobility. Various studies have focused on th ...

Frontiers Research Foundation2017

Simultaneous estimation of phase derivative and phase using parallel Kalman filter implementation

Pramod Rastogi, Rishikesh Dilip Kulkarni

This paper proposes a technique for the simultaneous estimation of interference phase derivative and phase from a complex interferogram recorded in an optical interferometric setup. The complex interferogram is represented as a spatially varying autoregres ...

2016

Multiple phase derivative estimation using autoregressive modeling in holographic interferometry

Pramod Rastogi, Rishikesh Dilip Kulkarni

A novel technique is proposed for the direct and simultaneous estimation of multiple phase derivatives from a deformation modulated carrier fringe pattern in a multi-wave holographic interferometry set-up. The fringe intensity is represented as a spatially ...

Institute of Physics2015

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

Seasonal variation of municipal solid waste generation and composition in four East European cities

Christian Ludwig

The quality of recyclable and residual municipal solid waste (MSW) is, among other factors, strongly influenced by the seasonal variation in MSW composition. However, a relatively marginal amount of published data on seasonal MSW composition especially in ...

Elsevier2014

Digital holographic moiré for the direct and simultaneous estimation of strain and slope fields

Pramod Rastogi, Rishikesh Dilip Kulkarni

A novel method is proposed for the direct and simultaneous estimation of multiple phase derivatives corresponding to strain and slope fields from a single moiré fringe pattern in digital holographic moiré. The interference field in a given row/column is a ...

Optical Society of America2014

Temporal Analysis of Motif Mixtures using Dirichlet Processes

Jean-Marc Odobez, Jagannadan Varadarajan, Rémi Emonet

In this article, we present a new model for unsupervised discovery of recurrent temporal patterns (or motifs) in time series (or documents). The model is designed to handle the difficult case of multivariate time series obtained from a mixture of activitie ...

2014

Spectral modeling of time series with missing data

Singular spectrum analysis is a natural generalization of principal component methods for time series data. In this paper we propose an imputation method to be used with singular spectrum-based techniques which is based on a weighted combination of the for ...

Elsevier2013

Damage detection using data-driven methods applied to moving-load responses

Ian Smith

Developed economies depend on complex and extensive systems of infrastructure to maintain economic prosperity and quality of life. In recent years, the implementation of Structural health monitoring (SHM) systems on full-scale bridges has increased. The go ...

Elsevier2013

A Hybrid Model-Free Data-Interpretation Approach For Damage Detection During Continuous Civil-Infrastructure Monitoring

Ian Smith, Ngoc Thanh Trinh, Irwanda Laory

A hard challenge associated with infrastructure monitoring is to extract useful information from large amounts of measurement data in order to detect changes in structures. This paper presents a hybrid model-free approach that combines two model-free metho ...

2012

Multivariate Spectral Analysis for Identifying the Brain Activations During Olfactory Perception

Touradj Ebrahimi, Jean-Marc Vesin, Ashkan Yazdani, Eleni Kroupi

Olfactory perception is a complex phenomenon associated with other processes such as cognition and emotion. Due to this complexity, there are still open issues and challenges regarding olfactory psychophysiology. One challenge concerns the investigation of ...

Ieee2012

Higher-Order Spectrum in Understanding Nonlinearity in EEG Rhythms

The fundamental nature of the brain's electrical activities recorded as electroencephalogram (EEG) remains unknown. Linear stochastic models and spectral estimates are the most common methods for the analysis of EEG because of their robustness, simplicity ...

2012

Novel complexity measurements in the ECG differentiate persistent from permanent atrial fibrillation

Jean-Marc Vesin, Laurent Renaud Uldry, Jérôme Sébastien Van Zaen, Lukas Kappenberger

Purpose: Distinguishing persistent from permanent atrial fibrillation (AF) in a reliable way would improve AF patient management, as cardioversion options could be considered appropriately. In this study, complexity measures based on the combined analysis ...

2011

Designing measurement systems for continuous monitoring of structures

Ian Smith, Nizar Bel Hadj Ali, Ngoc Thanh Trinh, Irwanda Laory

A good measurement system improves capability to identify the behavior of civil engineering structures. This paper presents a measurement-system design approach for continuous monitoring of structures. This approach performs two tasks: (1) determining the ...

2011

Measurement system design for damage detection using model-free data interpretation methods

Ian Smith, Nizar Bel Hadj Ali, Ngoc Thanh Trinh, Irwanda Laory

Designing a measurement system is usually performed using only engineering judgment and experience. Thus, it may result in either a large amount of redundant data or insufficient data leading to ambiguous results. This paper presents a systematic approach ...

2011

Analytical Footprints: Compact Representation of Elementary Singularities in Wavelet Bases

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

We introduce a family of elementary singularities that are point-Holder alpha-regular. These singularities are self-similar and are the Green functions of fractional derivative operators; i.e., by suitable fractional differentiation, one retrieves a Dirac ...

Institute of Electrical and Electronics Engineers2010