Publications of Catherine Charles
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See detailMulti-scale analysis of energy partitioning over a young beech forest using continuous wavelet transform
Bitton, Jonathan ULiege; Charles, Catherine ULiege; Heinesch, Bernard ULiege

Poster (2019, October 03)

Sensible (H) and latent (LE) heat are frequently studied forms of energy exchanges between an ecosystem and the atmosphere. The distribution of available energy between them reflects many underlying eco ... [more ▼]

Sensible (H) and latent (LE) heat are frequently studied forms of energy exchanges between an ecosystem and the atmosphere. The distribution of available energy between them reflects many underlying eco-physiological processes that may or not be linked. In order to identify these processes, this study investigates the evolution of both mentioned surface turbulent heat fluxes on an annual and multi-annual scale while taking their interactions into account. Its purpose is, firstly, to bring new insights on well-known H/LE patterns and, secondly, to derive underlying correlations between processes governing heat exchanges over an ecosystem. To achieve such objectives, a time-frequency analysis tool, namely the continuous wavelet transform, is implemented owing to its compatibility with the investigation of non-stationary phenomena. This methodology is applied on a fourteen-year dataset of half-hourly fluxes of H and LE obtained by eddy-covariance over a young beech forest at ICOS Hesse site, North-eastern France. Both the Morlet and Mexican Hat wavelets are used, due to their respective characteristics and their suitability for investigating environmental fluxes. At this stage, many wavelet-based results are available along with preliminary conclusions on the ecosystem’s behavior. In particular, this study highlights several periodic components at intermediate scales, ranging from days to years, throughout the growing season and links them to environmental drivers. Among these drivers, incident radiation and soil water content seem to play a key role in the energy partitioning of the forest ecosystem. Ultimately, this work explores the opportunities of long-term analyses of microclimatic measurements offered by the use of the continuous wavelet transform, which is expected to become an increasingly popular tool at the dawn of current global climate change. [less ▲]

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See detailMulti-scale analysis of the evolution of surface turbulent heat fluxes using continuous wavelet transform
Bitton, Jonathan ULiege; Charles, Catherine ULiege; Heinesch, Bernard ULiege

Poster (2019, June)

Sensible (H) and latent (LE) heat are frequently studied forms of energy exchanges between an ecosystem and the atmosphere. They result from many underlying processes that may or not be linked. In order ... [more ▼]

Sensible (H) and latent (LE) heat are frequently studied forms of energy exchanges between an ecosystem and the atmosphere. They result from many underlying processes that may or not be linked. In order to identify these processes, this study investigates the evolution of both mentioned surface turbulent heat fluxes on an annual and multi-annual scale while taking their correlations into account. To perform such analyses, a continuous wavelet-based methodology is applied on a fourteen-year dataset of half-hourly fluxes of H and LE obtained by a micrometeorological method called eddy-covariance over a young beech forest at Hesse, North-eastern France. Both the Morlet and Mexican Hat wavelets are used, due to their respective characteristics and their suitability for investigating environmental fluxes. This study – held in the case of a Master thesis – aims, firstly, to bring new insights on well-known H/LE patterns and, secondly, to derive underlying correlations between processes governing heat exchanges over an ecosystem. At this stage, many wavelet-based results are available along with preliminary conclusions on the ecosystem’s behavior. This communication presents the context of the research accompanied by key results, including the coherence spectra between H and LE, and exposes some difficulties encountered in the identification of eco-physiological processes driving both fluxes evolutions. [less ▲]

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See detailSoft Skills: how to make the young engineers aware of their new talents?
Colaux, Catherine ULiege; Beckers, Yves ULiege; Brostaux, Yves ULiege et al

in Stanzione, Joseph; Savelski, Mariane (Eds.) Creating the holistic engineer (2018)

The competency framework attached to the Life science engineering Master at Gembloux Agro-Bio Tech, University of Liege (Belgium) is composed of technical and scientific skills but also soft skills which ... [more ▼]

The competency framework attached to the Life science engineering Master at Gembloux Agro-Bio Tech, University of Liege (Belgium) is composed of technical and scientific skills but also soft skills which are not connected to academic courses. For the training of these skills, university needs the collaboration of the professional world. Therefore, the role of our teachers evolves towards a guiding or mentoring role. They will help students to analyse their professional experiences in order to shape their professional identity, to bring to light their acquired skills. This article describes how the portfolio, used as internship’s report, will help students to gain the self-confidence about their abilities and how professors can use these reflexive analyses to evaluate the acquisition of these soft skills. [less ▲]

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See detailAre we fully capturing the potential of solute breakthrough curves?
Prajara, Olivia; Köstel, Johannes; Charles, Catherine ULiege et al

Poster (2016)

Several studies have shown that preferential flow is a widespread phenomenon when studying solute transport in soil, but the relationships between this phenomenon, the hydrologic boundary conditions, and ... [more ▼]

Several studies have shown that preferential flow is a widespread phenomenon when studying solute transport in soil, but the relationships between this phenomenon, the hydrologic boundary conditions, and site properties are still only moderately understood. Even though a better understanding of these mechanisms is essential to improve predictions of the fate of the contaminants at short and long term time scales. Previous studies used nonparametric indicators characterizing the shape of breakthrough curves issued from Dirac tracer pulses to quantify preferential flow. Breakthrough curves are probability density functions obtained after controlled tracer application to soil columns and they are different for different soil types. Deconvolution techniques have been used to convert these BTC from different types of tracer application to standard transfer functions for which we can estimate and compare shape measures. However, previous studies suggest that the deconvolution used fits the tailing of the BTCs poorly which has an important impact of some of the shape measures used, since some of them are very sensitive to changes in the tailing. This study aims at improving the fit to the tailing of the BTC by using deconvolution techniques more appropriate for probability density functions specific to solute transport without assuming a specific shape of the transfer function. Deconvolution is a minimization of an objective function which is the sum of two terms. The first measures the fit of the solution to the experimental data and the second measures the smoothness of the solution. In this study the Kulblack-Leibler divergence will be applied instead of the widespread Euclidian norm for the first term. Kulblack-Leibler is specified for use with density probability functions and may therefore give a better compromise between fit of the main BTC and fit of the tailing. The innovative aspect of this work is that no a-priori assumptions are made concerning the shape of the BTC through the utilisation of a regularization term. These new convolution techniques will be tested and applied on BTCs from the solute transport data base constructed by Koestel et al. (2012).The expected results are an overview of the the goodness of fit to the probability density function and a quantification of the effect of these improved convolution techniques on the shape parameters. This study is located in the broader context to develop indicators that can predict the preferential flow for certain types of soil. [less ▲]

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See detailIntroduction aux problèmes inverses
Charles, Catherine ULiege

in Notes de Statistique et d'Informatique (2014)

cette note technique est une inititation aux problèmes inverses. Son objectif est d'expliquer au lecteur ses principes généraux, de montrer son large panel d'applications ainsi que de présenter ses ... [more ▼]

cette note technique est une inititation aux problèmes inverses. Son objectif est d'expliquer au lecteur ses principes généraux, de montrer son large panel d'applications ainsi que de présenter ses méthodes de résolution les plus courantes. [less ▲]

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See detailBlind Inverse Imaging with Positivity Constraints
Lecharlier, Loic; Charles, Catherine ULiege; De Mol, Christine

Book published by ULB (2014)

Dans les problèmes inverses en imagerie, on suppose généralement connu l’opéra- teur ou matrice décrivant le système de formation de l’image. De façon équiva- lente pour un système linéaire, on suppose ... [more ▼]

Dans les problèmes inverses en imagerie, on suppose généralement connu l’opéra- teur ou matrice décrivant le système de formation de l’image. De façon équiva- lente pour un système linéaire, on suppose connue sa réponse impulsionnelle. Toutefois, ceci n’est pas une hypothèse réaliste pour de nombreuses applica- tions pratiques pour lesquelles cet opérateur n’est en fait pas connu (ou n’est connu qu’approximativement). On a alors affaire à un problème d’inversion dite "aveugle". Dans le cas de systèmes invariants par translation, on parle de "décon- volution aveugle" car à la fois l’image ou objet de départ et la réponse impulsion- nelle doivent être estimées à partir de la seule image observée qui résulte d’une convolution et est affectée d’erreurs de mesure. Ce problème est notoirement dif- ficile et pour pallier les ambiguïtés et les instabilités numériques inhérentes à ce type d’inversions, il faut recourir à des informations ou contraintes supplémen- taires, telles que la positivité qui s’est avérée un levier de stabilisation puissant dans les problèmes d’imagerie non aveugle. La thèse propose de nouveaux al- gorithmes d’inversion aveugle dans un cadre discret ou discrétisé, en supposant que l’image inconnue, la matrice à inverser et les données sont positives. Le pro- blème est formulé comme un problème d’optimisation (non convexe) où le terme d’attache aux données à minimiser, modélisant soit le cas de données de type Poisson (divergence de Kullback-Leibler) ou affectées de bruit gaussien (moindres carrés), est augmenté par des termes de pénalité sur les inconnues du problème. La stratégie d’optimisation consiste en des ajustements alternés de l’image à re- construire et de la matrice à inverser qui sont de type multiplicatif et résultent de la minimisation de fonctions coût "surrogées" valables dans le cas positif. Le cadre assez général permet d’utiliser plusieurs types de pénalités, y compris sur la variation totale (lissée) de l’image. Une normalisation éventuelle de la réponse impulsionnelle ou de la matrice est également prévue à chaque itération. Des résultats de convergence pour ces algorithmes sont établis dans la thèse, tant en ce qui concerne la décroissance des fonctions coût que la convergence de la suite des itérés vers un point stationnaire. La méthodologie proposée est validée avec succès par des simulations numériques relatives à différentes applications telle que la déconvolution aveugle d’images en astronomie, la factorisation en matrices positives pour l’imagerie hyperspectrale et la déconvolution de densités en statistique. [less ▲]

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See detailDifferent methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review
Ly, Sarann ULiege; Charles, Catherine ULiege; Degré, Aurore ULiege

in Biotechnologie, Agronomie, Société et Environnement (2013), 17(2), 392-406

Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a ... [more ▼]

Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrological modeling. [less ▲]

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See detailLa représentation d'une matrice par biplot
Palm, Rodolphe ULiege; Charles, Catherine ULiege; Claustriaux, Jean-Jacques ULiege

in Notes de Statistique et d'Informatique (2012), (2), 1-22

Matrix factorization by means of singular value decomposition is examined and used to produce a graphical representation of a data matrix called biplot. The link between this biplot and the plots of the ... [more ▼]

Matrix factorization by means of singular value decomposition is examined and used to produce a graphical representation of a data matrix called biplot. The link between this biplot and the plots of the variables and of the individuals usually given in principal component analysis is discussed and applied to an example. [less ▲]

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See detailEffect of raingage density, position and interpolation on rainfall-discharge modelling
Ly, Sarann ULiege; Sohier, Catherine ULiege; Charles, Catherine ULiege et al

in Geophysical Research Abstracts (2012), 14(EGU2012), 2592

Precipitation traditionally observed using raingages or weather stations, is one of the main parameters that has direct impact on runoff production. This pPrecipitation data requires a preliminary spatial ... [more ▼]

Precipitation traditionally observed using raingages or weather stations, is one of the main parameters that has direct impact on runoff production. This pPrecipitation data requires a preliminary spatial interpolation prior to hydrological modeling. The accuracy of modelling result is determined bydepends on the accuracy of the interpolated spatial rainfall which differs according to different interpolation methods. The accuracy of the interpolated spatial rainfall is usually determined by cross-validation method. The objective of this study is to assess the different interpolation methods of daily rainfall at the watershed scale through hydrological modelling and to explore the best methods that provides a good long term simulation. Four versions of geostatistics: Ordinary Kriging (ORK), Universal Kriging (UNK), Kriging with External Dridft (KED) and Ordinary Cokriging (OCK) and two types of deterministic methods: Thiessen polygon (THI) and Inverse Distance Weighting (IDW) are used to produce 30-year daily rainfall inputs for a distributed physically-based hydrological model (EPIC-GRID). This work is conducted in the Ourthe and Ambleve nested catchments, located in the Ardennes hilly landscape in the Walloon region, Belgium. The total catchment area is 2908 km², lies between 67 and 693 m in elevation. The multivariate geostatistics (KED and OCK) are also used by incorporating elevation as external data to improve the rainfall prediction. This work also aims at analysing the effect of different raingage densities and position used for interpolation, on the stream flow modelled to get insight in terms of the capability and limitation of the geostatistical methods. The number of raingage varies from 70, 60, 50, 40, 30, 20, 8 to 4 stations located in and surrounding the catchment area. In the latter case, we try to use different positions: around the catchment and only a part of the catchment. The result shows that the simple method like THI fails to capture the rainfall and to produce good flow simulation when using 4 raingages. The KED and UNK are comparable to other methods for a raingage case that in which stations are located around the catchment area, especially in the high elevation catchment but the worst methods for other raingage position cases where the rainfall stations are located only at a part and mostly outside of the catchment area. However, three methods (IDW, ORK and OCK) can overcome this problem since they are more robust and can provide good performance of simulation in all raingage densities. When using 70, 60, 50, 40, 30, 20, 8 raingages in the catchment area (2908 km²), no substantial differences in model performance are observed. [less ▲]

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See detailGeostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium
Ly, Sarann ULiege; Charles, Catherine ULiege; Degre, Aurore ULiege

in Hydrology and Earth System Sciences (2011), 15(7), 2259-2274

Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to ... [more ▼]

Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably the interpolation with the Thiessen polygon, commonly used in various hydrological models. Integrating elevation into Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) did not improve the interpolation accuracy for daily rainfall. Ordinary Kriging (ORK) and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases. Care should be taken in applying UNK and KED when interpolating daily rainfall with very few neighbourhood sample points. These recommendations complement the results reported in the literature. ORK, UNK and KED using only spherical model offered a slightly better result whereas OCK using seven variogram models achieved better result. [less ▲]

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See detailIntroduction aux ondelettes
Charles, Catherine ULiege

in Notes de Statistique et d'Informatique (2011)

Cette note technique à caractère mathématique est une introduction aux ondelettes, un des outils d'analyse du signal. Son objectif est d'initier le lecteur à la théorie des ondelettes. Elle se découpe en ... [more ▼]

Cette note technique à caractère mathématique est une introduction aux ondelettes, un des outils d'analyse du signal. Son objectif est d'initier le lecteur à la théorie des ondelettes. Elle se découpe en deux parties. La première pose les bases théoriques des ondelettes. La deuxième partie traite des logiciels implémentés pour travailler avec les ondelettes. [less ▲]

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See detailIntroduction aux applications des ondelettes
Charles, Catherine ULiege

in Notes de Statistique et d'Informatique (2011)

Cette note fait suite à une note antérieure. Son objectif est de faire prendre conscience au lecteur de la large étendue d'applications des ondelettes. Elle se découpe en deux parties. La première ... [more ▼]

Cette note fait suite à une note antérieure. Son objectif est de faire prendre conscience au lecteur de la large étendue d'applications des ondelettes. Elle se découpe en deux parties. La première illustre la théorie des ondelettes aux moyens d'applications tournées vers la statistique. La deuxième se tourne vers les applications en traitement du signal et de l'image. [less ▲]

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See detailEffects of different spatial interpolators on the estimate of extreme precipitations
Ly, Sarann ULiege; Beckers, Eléonore ULiege; Charles, Catherine ULiege et al

in Geophysical Research Abstracts (2011), 13

The design values of the areal precipitation are needed for engineer to manage vital elements of our infrastructure. The areal precipitation can be generated by different interpolation methods. The ... [more ▼]

The design values of the areal precipitation are needed for engineer to manage vital elements of our infrastructure. The areal precipitation can be generated by different interpolation methods. The problem involves choosing the interpolation method that we should use to estimate the extreme event. This work aimed at analyzing the effects of different interpolation methods on the estimate of extreme events of daily areal precipitations at catchment scale. The extreme rainfalls were estimated using areal daily rainfall interpolated by several interpolation methods (Thiessen polygon, Inverse Distance Weighting, Ordinary Kriging, Universal Kriging, Kriging with an External Drift and Ordinary Cokriging). We used thirty-years-long daily time series and different density of rain gages (from 4 to 70 rain gages). Our study is located in the Ourthe and Ambleve catchment area (2908 km²) in the southern part of Belgium). Spatial interpolation with the geostatistical and Inverse Distance Weighting algorithms outperformed considerably interpolation with the Thiessen polygon. Kriging with an External Drift and Ordinary Cokriging presented the highest Root Mean Square Error between the geostatistical and Inverse Distance Weighting methods. Ordinary Kriging and Inverse Distance Weighting were considered to be the best methods, as they provided smallest Root Mean Square Error for nearly all cases. However, it’s not really the case of extreme estimates for particular return period. The extreme daily rainfall, corresponding to return periods of 25, 50 and 100 years, were computed by fitting of a statistical model to the series of maximum annual precipitation. These estimates were conducted using HYFRAN which allows us to fit 16 different statistical models, in 2 or 3 parameters. The most known are the models of Gumbel, Gamma, Weibull, exponential, Pareto, lognormale, Pearson III and GEV. Our results showed that the behaviour of extreme daily areal rainfall in this area was best described via the Gumbel and lognormal distributions. Using 70 rain gages, little differences in extreme rainfall were observed between the interpolation methods. The estimates from these methods were in the area of 95% confidence intervals of the estimates using the Thiessen polygon. However, when the number of rain gages diminishes, the Universal Kriging and Kriging with External drift methods produced extreme estimates outside the area of 95% confidence intervals of the estimates using the Thiessen polygon with all available stations. The analysis described here provides a means to choose the interpolation method in view to calculate extreme events. It shows to engineers or hydrologists the need for a particular care when working in the regions of sparse data. [less ▲]

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See detailSpatial interpolation of daily rainfall in Ourthe and Ambleve Basins, Belgium
Ly, Sarann ULiege; Sohier, Catherine ULiege; Charles, Catherine ULiege et al

in Geophysical Research Abstracts (2010, May)

Spatial interpolation of precipitation data is of great importance for hydrological modelling. The methods of geostatistics (krigings) become more popular to make spatial interpolation from point ... [more ▼]

Spatial interpolation of precipitation data is of great importance for hydrological modelling. The methods of geostatistics (krigings) become more popular to make spatial interpolation from point measurement to distributed hydrological models. However, most of existing geostatistic algorithms are available only for single-moment data. The first step of Kriging computation is the semi-variogramme modelling which usually uses only one variogramme model for all-day data. The objective of this paper is to review the implementation of an algorithm of spatial interpolation methods for daily rainfall and to compare the results of geostatistic and deterministic approaches. In this study, we will use daily rainfall data from 70 rain gauges in the hilly landscape of Ourthe and Ambleve Basins in Belgium (2751 km2). This area lies between 35 and 690 m in elevation and consists of river networks which are the tributaries of the Meuse River. The proposed algorithm will use the method of Cressie’s Approximate Weighted Least Squares to fit among sevens semi-variogramme models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) to daily sample semi-variogrammes. These seven models are computed on a daily basis. Firstly, one model is chosen by considering the minimum of least squares coefficient. Secondly, if the chosen model gives negative interpolated values, other models will be chosen again until the result become positive. Cross validation will be used to compare the interpolation performance of geostatistic to deterministic methods usually known as Thiessen polygon and Inverse DistanceWeighting (IDW). [less ▲]

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See detailIntroduction à Octave
Charles, Catherine ULiege

in Notes de Statistique et d'Informatique (2008)

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See detailIntroduction à Latex.
Charles, Catherine ULiege; Lecharlier, Loïc ULiege; Renaud, Frédéric

in Notes de Statistique et d'Informatique (2008)

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See detailXPS data analysis via Wavelets and Fourier Transform.
Charles, Catherine ULiege; Rasson, Jean-Paul; Leclerc, Gervais

in Surface and Interface Analysis (2004), 36

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See detailHREELS Signal Processing Via Wavelets.
Charles, Catherine ULiege; Leclerc, Gervais; Rasson, Jean-Paul

in Surface and Interface Analysis (2004), 36

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See detailWavelet Applications in Surface Science: a comparison to Fourier transform.
Charles, Catherine ULiege; Rasson, Jean-Paul; Pireaux, Jean-Jacques et al

in Surface and Interface Analysis (2004), 36

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See detailSome wavelet applications to signal and image processing.
Charles, Catherine ULiege

Doctoral thesis (2003)

Detailed reference viewed: 51 (6 ULiège)