Relevant bibliographies by topics / Observations Signal processing

Academic literature on the topic 'Observations Signal processing'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Observations Signal processing"

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Mudge, Todd D., and Rolf G. Lueck. "Digital Signal Processing to Enhance Oceanographic Observations." Journal of Atmospheric and Oceanic Technology 11, no. 3 (June 1994): 825–36. http://dx.doi.org/10.1175/1520-0426(1994)011<0825:dspteo>2.0.co;2.

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Padin, Stephen, and Schubert F. Soares. "Signal Processing Developments for the OVRO Array." International Astronomical Union Colloquium 140 (1994): 82–86. http://dx.doi.org/10.1017/s0252921100019187.

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Abstract An optical fiber IF transmission and tracking delay system and a wideband continuum correlator have been developed for the Owens Valley (OVRO) Millimeter Array. The IF system processes two 1-2 GHz bands which are frequency multiplexed through an optical fiber link. This allows simultaneous dual wavelength observations in the 2.7 and 1.3-mm bands or dual polarization observations in either band.
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Kumar, R. Suresh, and P. Manimegalai. "Detection and Separation of Eeg Artifacts Using Wavelet Transform." International Journal of Informatics and Communication Technology (IJ-ICT) 7, no. 3 (December 1, 2018): 149. http://dx.doi.org/10.11591/ijict.v7i3.pp149-156.

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Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real-time and recorded signals in multisensory instruments contains different and huge amount of noise, and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time-invariant filters. In this process, the input signal and the noise signal are assumed to achieve the linear output signal. During the process, the non-stationary signals arise in the bio-medical signal processing in addition to it there is no effective structure to deal with them. Wavelets transform has been proved to be the efficient tool for handling the non-stationary signals, but wavelet provide any possible way to approach multichannel signal processing. Based on the basic structure of linear estimation of non-stationary multichannel data and statistical models of spatial signal coherence acquire through the wavelet transform in multichannel estimation. The above methods can be used for Electroencephalography (EEG) signal denoising through the original signal and then implement the noise reduction technique to evaluate their performance such as SNR, MSE and computation time.
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Lucjan Setlak and Rafał Kowalik. "E1 Signal Processing of the Galileo System in the Navigation Receiver." Communications - Scientific letters of the University of Zilina 23, no. 3 (July 1, 2021): E46—E55. http://dx.doi.org/10.26552/com.c.2021.3.e46-e55.

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The subject of this article are issues related to the navigation system in the field of analyzing the processed signal in the GNSS system receiver. The main purpose of the work is to discuss the Galileo E1 signal processing methods in the GNSS navigation system receiver, supported by adapted research tools in terms of solving the research problem (analysis, model, simulation tests) and the mathematical apparatus used. Key studies are concentrated around the process of generating the navigation data, dispersing sequences and signal modulation. Thus, when designing a receiver, it is better to use the simulation signals than the real ones, since one can get more control over the properties of the received signal. In the final part of the work, in accordance with the subject of research, based on the developed appropriate research tools, observations and final conclusions were formulated, which have practical applications.
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Schroth, Arno, Karl Tragi, Ernst Lüneburg, and Madhukar Chandra. "Polarimetric signal processing of meteorological target observations with the DLR weather radar." European Transactions on Telecommunications 3, no. 4 (July 1992): 381–98. http://dx.doi.org/10.1002/ett.4460030411.

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Ogunfunmi, Tokunbo. "Adaptive Signal Processing and Machine Learning Using Entropy and Information Theory." Entropy 24, no. 10 (October 8, 2022): 1430. http://dx.doi.org/10.3390/e24101430.

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Möller, Gregor, and Daniel Landskron. "Atmospheric bending effects in GNSS tomography." Atmospheric Measurement Techniques 12, no. 1 (January 3, 2019): 23–34. http://dx.doi.org/10.5194/amt-12-23-2019.

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Abstract. In Global Navigation Satellite System (GNSS) tomography, precise information about the tropospheric water vapor distribution is derived from integral measurements like ground-based GNSS slant wet delays (SWDs). Therefore, the functional relation between observations and unknowns, i.e., the signal paths through the atmosphere, have to be accurately known for each station–satellite pair involved. For GNSS signals observed above a 15∘ elevation angle, the signal path is well approximated by a straight line. However, since electromagnetic waves are prone to atmospheric bending effects, this assumption is not sufficient anymore for lower elevation angles. Thus, in the following, a mixed 2-D piecewise linear ray-tracing approach is introduced and possible error sources in the reconstruction of the bended signal paths are analyzed in more detail. Especially if low elevation observations are considered, unmodeled bending effects can introduce a systematic error of up to 10–20 ppm, on average 1–2 ppm, into the tomography solution. Thereby, not only the ray-tracing method but also the quality of the a priori field can have a significant impact on the reconstructed signal paths, if not reduced by iterative processing. In order to keep the processing time within acceptable limits, a bending model is applied for the upper part of the neutral atmosphere. It helps to reduce the number of processing steps by up to 85 % without significant degradation in accuracy. Therefore, the developed mixed ray-tracing approach allows not only for the correct treatment of low elevation observations but is also fast and applicable for near-real-time applications.
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Yardim, Caglar, Peter Gerstoft, and Zoi-Heleni Michalopoulou. "Geophysical signal processing using sequential Bayesian techniques." GEOPHYSICS 78, no. 3 (May 1, 2013): V87—V100. http://dx.doi.org/10.1190/geo2012-0180.1.

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Sequential Bayesian techniques enable tracking of evolving geophysical parameters via sequential observations. They provide a formulation in which the geophysical parameters that characterize dynamic, nonstationary processes are continuously estimated as new data become available. This is done by using prediction from previous estimates of geophysical parameters, updates stemming from physical and statistical models that relate seismic measurements to the unknown geophysical parameters. In addition, these techniques provide the evolving uncertainty in the estimates in the form of posterior probability density functions. In addition to the particle filters (PFs), extended, unscented, and ensemble Kalman filters (EnKFs) were evaluated. The filters were compared via reflector and nonvolcanic tremor tracking examples. Because there are numerous geophysical problems in which the environmental model itself is not known or evolves with time, the concept of model selection and its filtering implementation were introduced. A multiple model PF was then used to track an unknown number of reflectors from seismic interferometry data. We found that when the equations that define the geophysical problem are strongly nonlinear, a PF was needed. The PF outperformed all Kalman filter variants, especially in low signal-to-noise ratio tremor cases. However, PFs are computationally expensive. The EnKF is most appropriate when the number of parameters is large. Because each technique is ideal under different conditions, they complement each other and provide a useful set of techniques for solving sequential geophysical inversion problems.
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Sirri, Paul, Elizabeth M. Palmer, and Essam Heggy. "Processing and Analysis for Radio Science Experiments (PARSE): Graphical Interface for Bistatic Radar." Planetary Science Journal 3, no. 1 (January 1, 2022): 24. http://dx.doi.org/10.3847/psj/ac3a07.

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Abstract Opportunistic bistatic radar (BSR) observations of planetary surfaces can probe the textural and electrical properties of several solar system bodies without needing a dedicated instrument or additional mission requirements, providing unique insights into volatile enrichment and supporting future landing, anchoring, and in situ sampling. Given their opportunistic nature, complex observation geometries, and required radiometric knowledge of the received radio signal, these data are particularly challenging to process, analyze, and interpret for most planetary science data users, who can be unfamiliar with link budget analysis of received echoes. The above impedes real-time use of BSR data to support mission operations, such as identifying safe landing locations on small bodies, as was the case for the Rosetta mission. To address this deficiency, we develop an open-source graphical user interface—Processing and Analysis for Radio Science Experiments (PARSE)—that assesses the feasibility of performing BSR observations and automates radiometric signal processing, power spectral analysis, and visualization of DSN planetary radio science data sets acquired during mission operations or archived on NASA’s Planetary Data System. In this first release, PARSE automates the processing chain developed for Dawn at Asteroid Vesta, streamlining the detection of DSN-received surface-scatter echoes generated as the spacecraft enters/exits occultations behind the target. Future releases will include support for existing Arecibo data sets and other Earth-based radio observatories. Our tool enables the broader planetary science community, beyond planetary radar signal processing experts, to utilize BSR data sets to characterize electrical and textural properties of planetary surfaces. Such tools are becoming increasingly important as the number of space missions—and subsequent opportunities for orbital radio science observations—continue to grow.
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Xu, Pengfei, Yinjie Jia, and Mingxin Jiang. "Blind audio source separation based on a new system model and the Savitzky-Golay filter." Journal of Electrical Engineering 72, no. 3 (June 1, 2021): 208–12. http://dx.doi.org/10.2478/jee-2021-0029.

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Abstract Blind source separation (BSS) is a research hotspot in the field of signal processing. This scheme is widely applied to separate a group of source signals from a given set of observations or mixed signals. In the present study, the Savitzky-Golay filter is applied to smooth the mixed signals, adopt a simplified cost function based on the signal to noise ratio (SNR) and obtain the demixing matrix accordingly. To this end, the generalized eigenvalue problem is solved without conventional iterative methods. It is founded that the proposed algorithm has a simple structure and can be easily implemented in diverse problems. The obtained results demonstrate the good performance of the proposed model for separating audio signals in cases with high signal to noise ratios.
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Dissertations / Theses on the topic "Observations Signal processing"

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Armstrong, Richard Paul. "High-performance signal processing architectures for digital aperture array telescopes." Thesis, University of Oxford, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.560917.

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An instrument with the ability to image neutral atomic hydrogen (HI) to cosmic redshift will allow the fundamental properties of the Universe to be more precisely determined; in particular the distribution, composition, and evolutionary history of its matter and energy. The Square Kilometre Array (SKA) is a radio survey telescope conceived with this aim. It will have the observational potential for much further fundamental science, including strong field tests of gravity and general relativity, revealing the origin and history of cosmological re-ionisation and magnetism, direct measures of gravitational radiation, and surveys of the unmapped Universe. And it is the advance of instrumentation that will enable it. This thesis makes three central contributions to radio instrumentation. Digital aperture arrays are a collector technology proposed for the key low- and mid- frequency ranges targeted by the SKA that have the potential to provide both the collecting area and field of view required for deep, efficient all-sky surveys of HI. The 2-Polarisations, All Digital (2-PAD) aperture array is an instrumental pathfinder for the SKA, novel in being a densely-spaced, wide-band aperture array that performs discrete signal filtering entirely digitally. The digital design of the 2-PAD radio receiver and the deployment of the aperture array and signal processing system at Jodrell Bank Radio Observatory is detailed in this thesis. The problem of element anisotropy in small arrays, the atomic unit of the SKA station array, ultimately affects beam quality. Addressing this issue, a metaheuristic digital beam-shape optimisation technique is applied to a small beamformed array, and is shown to outperform traditional analytic solutions. Digital processing for aperture arrays is challenging. A qualitative framework shows that energy, computational and communication requirements demand optimised processing architectures. A quantitative model reveals the physical limitations on architecture choice. An energy-optimised architecture, the IBM BIT integer array processor, is investigated in detail; a cycle-accurate architectural simulator and programming language are developed and used to build signal processing algorithms on the array architecture.
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Lane, Dallas W. "Signal processing methods for airborne lidar bathymetry." Title page, table of contents and abstract only, 2001. http://web4.library.adelaide.edu.au/theses/09ENS/09ensl265.pdf.

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"August 2001." Includes bibliographical references (leaves 77-80). Examines the susceptibility of existing signal processing methods to errors and identifies other possible causes of depth error not accounted for by existing signal processing methods, by analysis of the detected laser return waveform data. Methods to improve depth accuracy are investigated.
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Paubert, Gabriel. "Instrumentation pour le radiotélescope de 30 mètres de l'IRAM et observations d'atmosphères planétaires." Phd thesis, Université Joseph Fourier (Grenoble), 1992. http://tel.archives-ouvertes.fr/tel-00688090.

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Les exigences en matière de stabilité et de linéarité des instruments utilisés en radioastronomie sont particulièrement sévères. Ce mémoire présente la conception et la réalisation d'un détecteur continuum adapté à ce cahier des charges. Une étude théorique démontre que le détecteur à diode Schottky ne répond pas à ces besoins. L'instrument finalement réalisé, construit à partir d'une diode tunnel, possède un bruit proche de la limite physique fondamentale. Il reste cependant très simple. Le chapitre suivant est consacré à l'étude et à la réalisation de l'électronique d'acquisition d'un spectrographe acousto-optique à large bande et à l'etude de ses caractéristiques dans des conditions d'utilisation réelles. Il inclut la description d'une méthode simple qui permet de s'affranchir des erreurs de linéarité différentielle du convertisseur analogique-numérique. La validation des caractéristiques du spectrographe s'appuie sur la comparaison avec deux batteries de filtres identiques. Sur le plan scientifique, il présente l'observation d'objets du système solaire entourés d'une atmosphère et l'interprétation des résultats dans le cas de Titan.
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Castaings, Thibaut. "Catalogage de petits débris spatiaux en orbite basse par observations radars isolées." Phd thesis, Grenoble, 2014. http://tel.archives-ouvertes.fr/tel-00955486.

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Les débris spatiaux sont devenus une menace considérable pour la viabilité des satellites opérationnels en orbite basse. Afin de pouvoir éviter des collisions accidentelles, des systèmes de surveillance de l'espace existent mais sont limités en performances de détection pour les objets de petite taille (diamètre inférieur à 10cm), ce qui pousse à l'étude de nouvelles solutions. Cette thèse a pour objectif d'appuyer la faisabilité d'un système radar au sol utilisant un champ de veille étroit pour le catalogage de petits débris en orbite basse. Un tel système fournirait en effet des observations dites " isolées ", c'est-à-dire qu'une orbite n'est pas immédiatement déductible de chacune d'entre elles. Le grand nombre combinaisons nécessaires est alors prohibitif en termes de temps de calcul pour la résolution de ce problème de pistage. Nous proposons dans ces travaux une nouvelle méthode pour initialiser les pistes, c'est-à-dire associer des observations isolées avec une faible ambiguïté et en déduire des orbites précises. Les pistes ainsi obtenues sont combinées et filtrées grâce à un algorithme de pistage multicible que nous avons adapté aux particularités du problème. Avec un taux de couverture de plus de 80% obtenu en temps réel sur 3 jours pour des scénarios de 500 à 800 objets en plus d'un fort taux de fausses alarmes, les performances de la méthode proposée tendent à prouver la faisabilité du système envisagé. Afin d'extrapoler les résultats obtenus à de plus fortes densités d'observations, nous proposons un modèle de complexité combinatoire calibré sur les performances de l'algorithme aux faibles densités. L'apport d'un second capteur identique est également étudié et met en évidence un point de compromis entre réactivité et complexité combinatoire, ce qui offre un degré de liberté supplémentaire dans la conception d'un tel système.
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Revillon, Guillaume. "Uncertainty in radar emitter classification and clustering." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS098/document.

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En Guerre Electronique, l’identification des signaux radar est un atout majeur de la prise de décisions tactiques liées au théâtre d’opérations militaires. En fournissant des informations sur la présence de menaces, la classification et le partitionnement des signaux radar ont alors un rôle crucial assurant un choix adapté des contre-mesures dédiées à ces menaces et permettant la détection de signaux radar inconnus pour la mise à jour des bases de données. Les systèmes de Mesures de Soutien Electronique enregistrent la plupart du temps des mélanges de signaux radar provenant de différents émetteurs présents dans l’environnement électromagnétique. Le signal radar, décrit par un motif de modulations impulsionnelles, est alors souvent partiellement observé du fait de mesures manquantes et aberrantes. Le processus d’identification se fonde sur l’analyse statistique des paramètres mesurables du signal radar qui le caractérisent tant quantitativement que qualitativement. De nombreuses approches mêlant des techniques de fusion de données et d’apprentissage statistique ont été développées. Cependant, ces algorithmes ne peuvent pas gérer les données manquantes et des méthodes de substitution de données sont requises afin d’utiliser ces derniers. L’objectif principal de cette thèse est alors de définir un modèle de classification et partitionnement intégrant la gestion des valeurs aberrantes et manquantes présentes dans tout type de données. Une approche fondée sur les modèles de mélange de lois de probabilités est proposée dans cette thèse. Les modèles de mélange fournissent un formalisme mathématique flexible favorisant l’introduction de variables latentes permettant la gestion des données aberrantes et la modélisation des données manquantes dans les problèmes de classification et de partionnement. L’apprentissage du modèle ainsi que la classification et le partitionnement sont réalisés dans un cadre d’inférence bayésienne où une méthode d’approximation variationnelle est introduite afin d’estimer la loi jointe a posteriori des variables latentes et des paramètres. Des expériences sur diverses données montrent que la méthode proposée fournit de meilleurs résultats que les algorithmes standards
In Electronic Warfare, radar signals identification is a supreme asset for decision making in military tactical situations. By providing information about the presence of threats, classification and clustering of radar signals have a significant role ensuring that countermeasures against enemies are well-chosen and enabling detection of unknown radar signals to update databases. Most of the time, Electronic Support Measures systems receive mixtures of signals from different radar emitters in the electromagnetic environment. Hence a radar signal, described by a pulse-to-pulse modulation pattern, is often partially observed due to missing measurements and measurement errors. The identification process relies on statistical analysis of basic measurable parameters of a radar signal which constitute both quantitative and qualitative data. Many general and practical approaches based on data fusion and machine learning have been developed and traditionally proceed to feature extraction, dimensionality reduction and classification or clustering. However, these algorithms cannot handle missing data and imputation methods are required to generate data to use them. Hence, the main objective of this work is to define a classification/clustering framework that handles both outliers and missing values for any types of data. Here, an approach based on mixture models is developed since mixture models provide a mathematically based, flexible and meaningful framework for the wide variety of classification and clustering requirements. The proposed approach focuses on the introduction of latent variables that give us the possibility to handle sensitivity of the model to outliers and to allow a less restrictive modelling of missing data. A Bayesian treatment is adopted for model learning, supervised classification and clustering and inference is processed through a variational Bayesian approximation since the joint posterior distribution of latent variables and parameters is untractable. Some numerical experiments on synthetic and real data show that the proposed method provides more accurate results than standard algorithms
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Bourien, Jérôme. "Analyse de distributions spatio-temporelles de transitoires dans des signaux vectoriels. Application à la détection-classification d'activités paroxystiques intercritiques dans des observations EEG." Phd thesis, Université Rennes 1, 2003. http://tel.archives-ouvertes.fr/tel-00007178.

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Les signaux électroencéphalographiques enregistrés chez les patients épileptiques reflètent, en dehors des périodes correspondant aux crises d'épilepsie, des signaux transitoires appelés "activités épileptiformes" (AE). L'analyse des AE peut contribuer à l'étude des épilepsies partielles pharmaco-résistantes. Une méthode de caractérisation de la dynamique spatio-temporelle des AE dans des signaux EEG de profondeur est présentée dans ce document. La méthode est constituée de quatre étapes:

1. Détection des AE monovoie. La méthode de détection, qui repose sur une approche heuristique, utilise un banc de filtres en ondelettes pour réhausser la composante pointue des AE (généralement appelée "spike" dans la littérature). La valeur moyenne des statistiques obtenues en sortie de chaque filtre est ensuite analysée avec un algorithme de Page-Hinkley dans le but de détecter des changements abrupts correspondant aux spikes.

2. Fusion des AE. Cette procédure recherche des co-occurrences entre AE monovoie à l'aide d'une fenêtre glissante puis forme des AE multivoies.

3. Extraction des sous-ensembles de voies fréquement et significativement activées lors des AE multivoies (appelés "ensembles d'activation").

4. Evaluation de l'éxistence d'un ordre d'activation temporel reproductible (éventuellement partiel) au sein de chaque ensemble d'activation.

Les méthodes proposées dans chacune des étapes ont tout d'abord été évaluées à l'aide de signaux simulés (étape 1) ou à l'aide de models Markoviens (étapes 2-4). Les résultats montrent que la méthode complète est robuste aux effets des fausses-alarmes. Cette méthode a ensuite été appliquée à des signaux enregistrés chez 8 patients (chacun contenant plusieurs centaines d'AE). Les résultats indiquent une grande reproductibilité des distributions spatio-temporelles des AE et ont permis l'identification de réseaux anatomo-fonctionnels spécifiques.
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Berthier, Sébastien. "Complémentarité et représentativité des observations atmosphériques effectuées par instrumentation active et passive sur les nouvelles plates-formes spatiales." Phd thesis, Université de Versailles-Saint Quentin en Yvelines, 2007. http://tel.archives-ouvertes.fr/tel-00327231.

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Un des objectifs majeurs des programmes de recherches actuels est de comprendre quel est l'impact des nuages et des aérosols au sein du bilan radiatif global. En effet, les nuages et les aérosols ont une influence significative sur la balance radiative terrestre, et induisent des réponses climatiques diverses qui ne sont pas encore pleinement connues. L'hétérogénéité spatiale des structures nuageuses et de leurs propriétés microphysiques, contribue de manière significative à la modulation du budget énergétique terrestre. Les flux radiatifs pris à la surface sont très sensibles à la structure éométrique de ces nuages, ainsi qu'à leur altitude. Un des premiers objectifs afin d'améliorer les modèles climatiques existant, est donc d'acquérir une meilleur connaissance sur la distribution tri- dimensionnelle des structures nuageuses. Les systèmes spatiaux comportant des instrumentations lidar nous apportent aujourd'hui de nouvelles informations sur la distribution verticale des aérosols. Notre second objectif est donc d'améliorer l'obtention des propriétés des aérosols au dessus des surfaces continentales, lieu ou l'obtention de résultat via les systèmes de détection passif sont connus pour être difficiles du fait de la contribution radiative de la surface. Afin de remplir le premier objectif, nous avons appliqué et adapté un algorithme nous permettant d'estimer la fonction de densité de probabilité du sommet des structures nuageuses, à partir des profils lidar fournis par la mission satellite GLAS (Geoscience Laser Altimeter System, NASA) et la mission LITE (In-space Technology Experiment, NASA, 1994). La méthodologie utilisée est dans un premier temps expliquée. Les résultats obtenus grâce à l'utilisation des données GLAS et LITE sont présentés et discutés. La validation de cette méthode du point de vue de ses performances est ensuite effectuée grâce à une étude de sensibilité. La synergie entre les mesures des instruments passifs et actifs peut amener à des améliorations significatives de l'inversion lidar. Dans le but de remplir notre second objectif, nous présentons alors dans la suite de ce travail le potentiel apporté par l'utilisation du couplage entre un lidar spatial (LITE en l'occurrence) et un satellite géostationnaire (Meteosat-5) afin de retrouver les propriétés optiques de l'aérosol au dessus des océans et des continents, dans le cas particulier des poussières désertiques Africaines. Pour ce faire, un algorithme a été implémenté. Les résultats fournis par cette méthode sont présentés. Les erreurs faites sur l'estimation de l'impact radiatif de l'aérosol sont estimées pour cette synergie, mais aussi dans le cas des autres synergies possibles pouvant allier les instruments de télédétection actifs et passifs, embarqués à bord des satellites actuellement en orbite.
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Perret, Benjamin. "Caractérisation multibande de galaxies par hiérarchie de modèles et arbres de composantes connexes." Phd thesis, Université de Strasbourg, 2010. http://tel.archives-ouvertes.fr/tel-00559584.

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Cette thèse propose une méthode de caractérisation morphologique multibande des galaxies. Ces dernières ont commencé à évoluer et à interagir très tôt dans l'histoire de l'Univers: leurs formes dans les différentes parties du spectre électromagnétique représentent donc un traceur important de cette histoire. Ce travail propose une organisation hiérarchique de modèles, allant de la description des structures dominantes (bulbe et disque) aux composantes les plus fines (bras spiraux, anneaux, ...). Elle permet d'aboutir à une description des galaxies de haut niveau sémantique, chaque modèle réalisant une décomposition multibande de l'image en composantes astrophysiques interprétables par les astronomes. Les modélisations proposées innovent par l'intégration d'un filtre adaptatif appliqué sur les observations, dont les paramètres sont estimés conjointement avec ceux des composantes de la galaxie. L'estimation des paramètres des modèles est effectuée dans un contexte bayésien et résolue à l'aide d'algorithmes d'optimisation stochastique (algorithmes de Monte Carlo par chaines de Markov). La rapidité des algorithmes est améliorée grâce à des techniques d'échelles et de directions adaptatives, ainsi qu'à une version multi-températures du recuit simulé. En outre, les développements concernant la théorie des arbres de composantes connexes permettent la mise au point d'algorithmes non paramétriques multibandes, efficaces et robustes pour la réalisation des pré-traitements nécessaires à la mise en oeuvre de la décomposition en structures. Cela a notamment abouti à des avancées dans la théorie des hyperconnexions et des représentations sous forme d'arbres de composantes hyperconnexes. Les performances des méthodes proposées ont été évaluées sur un ensemble conséquent d'environ 1 500 galaxies et discutées avec les astronomes: elles montrent clairement la pertinence et la robustesse de la méthode. Ces résultats ouvrent la voie à de nouvelles classifications prenant en compte la signature multibande des galaxies spatialement résolues.
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Uzuegbunam, Nkiruka M. A. "SELF-IMAGE MULTIMEDIA TECHNOLOGIES FOR FEEDFORWARD OBSERVATIONAL LEARNING." UKnowledge, 2018. https://uknowledge.uky.edu/ece_etds/124.

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This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in delivering behavioral interventions for young children on the autism spectrum.
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Galle, Sylvie. "Analyse des champs spatiaux par utilisation de la télédétection : estimation de la durée quotidienne d'insolation en France à l'aide d'images du satellite Météosat et de mesures sol." Phd thesis, Grenoble INPG, 1987. http://tel.archives-ouvertes.fr/tel-00694114.

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L'insolation est étudiée, à l'échelle synoptique (la France) à l'aide d'un ensemble de mesures de la durée quotidienne d'insolation réalisées au sol et par télédétection satellitaire. L'objectif poursuivi est d'analyser une série de données suffi* samment longue pour caractériser de manière statistique le comportement climatologique de l'insolation dans l'espace. Les données sont fournies par 88 héliographes du réseau synoptique français ainsi que par le programme " Cactus " de la Météorologie Nationale, qui utilise les images visibles du satellite Météosat. L'étude porte sur une année de données. La similarité de la structure spatiale des mesures du sol et du satellite est montrée par analyse objective, et par analyse en composantes principales de processus. La fine perception de la variabilité spatiale du satellite est alors utilisée pour optimiser un réseau de mesures au sol. Les performances du programme Cactus sont comparées avec celles de méthodes d'interpolation classiques (basées sur 23 héliographes), pour l'estimation du rapport d'insolation. Elles se sont révélées plus performantes en terme de cofluctuation. Il apparaît cependant une tendance du satellite à exagérer les valeurs extrêmes. L'étalonnage des mesures satellitaires par des mesures sol a pour but de conjuguer les qualités de précision des hélio* graphes, et la définition spatiale du satellite. Une approche géostatistique est proposée. L'effet recherché est observé à partir d'une certaine densité du réseau d'étalonnage
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Books on the topic "Observations Signal processing"

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service), SpringerLink (Online, ed. Mathematical SETI: Statistics, Signal Processing, Space Missions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Jinsoo, Bae, and Ki Sun Yong 1968-, eds. Advanced theory of signal detection: Weak signal detection in generalized observations. Berlin: Springer, 2002.

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Li, Jian, Ph. D., 1965- and Stoica Petre, eds. Spectral analysis of signals: The missing data case. [San Rafael, Calif.]: Morgan & Claypool Publishers, 2005.

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He, Qi. System Identification Using Regular and Quantized Observations: Applications of Large Deviations Principles. New York, NY: Springer New York, 2013.

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Liège International Astrophysical Colloquium (27th 1987). Observational astrophysics with high precision data: Proceedings of the 27th Liège International Astrophysical Colloquium, June 23-26, 1987. Cointe-Ougrée, Belgique: Université de Liège, Institut d'astrophysique, 1987.

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Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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United States. National Telecommunications and Information Administration., ed. Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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Song, Iickho, Jinsoo Bae, Sun Yong Kim, J. Bae, and S. Y. Kim. Advanced Theory of Signal Detection: Weak Signal Detection in Generalized Observations (Signals and Communication Technology). Springer, 2004.

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Maccone, Claudio. Mathematical SETI: Statistics, Signal Processing, Space Missions. Springer, 2017.

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Book chapters on the topic "Observations Signal processing"

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Liu, Jing, Mahendra Mallick, Feng Lian, and Kaiyu Huang. "A Novel Compressed Sensing–Based Algorithm for Space–Time Signal Processing Using Airborne Radars." In Compressive Sensing of Earth Observations, 131–52. Boca Raton, FL : Taylor & Francis, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315154626-6.

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Ikuta, Akira, and Hisako Orimoto. "Static and Dynamic Methods for Fuzzy Signal Processing of Sound and Electromagnetic Environment Based on Fuzzy Observations." In Studies in Computational Intelligence, 171–87. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26393-9_11.

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Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. "Application to Signal Processing: Using 1-D Radar Observations to Detect a Space Explosion Core among the Explosion Fragments." In Computing Statistics under Interval and Fuzzy Uncertainty, 289–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1_36.

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Fukao, Shoichiro, and Kyosuke Hamazu. "Reception and Processing of Signals." In Radar for Meteorological and Atmospheric Observations, 105–66. Tokyo: Springer Japan, 2013. http://dx.doi.org/10.1007/978-4-431-54334-3_5.

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Blanchet, Gérard, and Maurice Charbit. "Spectral Observation." In Digital Signal and Image Processing Using Matlab®, 95–113. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118999554.ch3.

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Liu, Bingchao, and Zhiquan Feng. "Integrate Hand Constraints with Image Features to Build an Observation Model for Hand Tracking." In Multimedia and Signal Processing, 459–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_58.

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Sun, Licun, Yuanfangzhou Wang, Linhai Li, Jie Feng, Ya Liu, and Shuwu Sheng. "The Observation and Simulation of Dynamic Diffraction Patterns Caused by a Cylindrical Liquid Diffusion Pool for Diffusivity Measurement." In New Approaches for Multidimensional Signal Processing, 243–54. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4676-5_20.

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Lee, Sang Won, Kwang Sun Ryu, Jae Ho Kim, Na Young You, Ha Ye Jin Kang, Yong Ha Hwang, Kui Son Choi, and Hyo Soung Cha. "Avoid Selection Bias in Observational Study Based on Health Big Data." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 262–67. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6420-2_32.

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Doviak, Richard J., and Dušan S. Zrnić. "Weather Signal Processing." In Doppler Radar and Weather Observations, 122–59. Elsevier, 1993. http://dx.doi.org/10.1016/b978-0-12-221422-6.50011-5.

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Breva, Yannick, Johannes Kröger, Tobias Kersten, and Steffen Schön. "Estimation and Validation of Codephase Center Correction Using the Empirical Mode Decomposition." In International Association of Geodesy Symposia. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/1345_2022_159.

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AbstractIn high precision Global Navigation Satellite Systems (GNSS) applications, it is necessary to take phase center corrections (PCC) into account. Beside these corrections for carrier phase measurements, also corrections for the codephase are necessary, so called codephase center corrections (CPC). The CPC, also known as group delay variations, are antenna dependent delays of the received codephase, which are varying with azimuth and elevation of the incoming GNSS signal. A concept for estimating absolute CPC and PCC for multi GNSS signals has been established by the Institut für Erdmessung.In this paper, the standard calibration approach with a sampling rate of 1 Hz is briefly described, which works well for PCC estimation. The main challenge of this approach for estimating repeatable CPC patterns is the significantly higher noise to pattern ratio in the observations compared to PCC determination. Therefore, an alternative processing strategy is presented in this contribution. By increasing the sampling rate to 10 Hz, the empirical mode decomposition can be used to reduce the noise of the input observations by maintaining all pattern information. With this method, the calibration repeatability is improved by 46% to 60% for GPS and Galileo C1C signals for a geodetic antenna. Moreover, the estimated pattern is validated in the positioning domain with a single point positioning approach. By considering the estimated CPC the accuracy of the height component can be improved.
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Conference papers on the topic "Observations Signal processing"

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Candes, Emmanuel, and Justin Romberg. "Robust Signal Recovery from Incomplete Observations." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312579.

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Shah, Viraj, and Chinmay Hegde. "Signal Reconstruction From Modulo Observations." In 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2019. http://dx.doi.org/10.1109/globalsip45357.2019.8969100.

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Wang, Jing, and Guangqiang Liu. "Analysis and Processing of L-band Radar Signal Sudden Failure." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9026062.

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Kim, Pyung-Soo, and Jeong Hun Choi. "A new fixed-lag smoother using recent finite observations." In Signal Processing (ICICS). IEEE, 2009. http://dx.doi.org/10.1109/icics.2009.5397660.

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Wei, Zhang, Yang Jie, Pu Li, Cheng Bing, and Li Chunhu. "Design and Implementation of Signal Processing for Software Doppler Weather Radar." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9076590.

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Caromi, Raied, Yan Xin, and Lifeng Lai. "Fast multichannel spectrum scanning with multiple simultaneous observations." In Signal Processing (WCSP 2010). IEEE, 2010. http://dx.doi.org/10.1109/wcsp.2010.5634039.

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Chen, Hao, and Tsang-Yi Wang. "Impact of common observations in parallel distributed detection." In 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE). IEEE, 2015. http://dx.doi.org/10.1109/dsp-spe.2015.7369534.

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Combettes, Patrick L., and Zev C. Woodstock. "Signal Recovery from Inconsistent Nonlinear Observations." In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9746145.

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Garello, Rene. "Signal and image processing applications in radar ocean observations." In 2010 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA). IEEE, 2010. http://dx.doi.org/10.1109/isspa.2010.5605405.

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Zitzmann, Cathel, Remi Cogranne, Florent Retraint, Igor Nikiforov, Lionel Fillatre, and Philippe Cornu. "Hypothesis testing by using quantized observations." In 2011 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2011. http://dx.doi.org/10.1109/ssp.2011.5967743.

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Reports on the topic "Observations Signal processing"

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Steffens, John C., and Eithan Harel. Polyphenol Oxidases- Expression, Assembly and Function. United States Department of Agriculture, January 1995. http://dx.doi.org/10.32747/1995.7571358.bard.

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Polyphenol oxidases (PPOs) participate in the preparation of many plant products on the one hand and cause considerable losses during processing of plant products on the other hand. However, the physiological functions of plant PPO were still a subject of controversy at the onset of the project. Preliminary observations that suggested involvement of PPOs in resistance to herbivores and pathogens held great promise for application in agriculture but required elucidation of PPO's function if modulation of PPO expression is to be considered for improving plant protection or storage and processing of plant products. Suggestions on a possible role of PPO in various aspects of chloroplast metabolism were also relevant in this context. The characterization of plant PPO genes opened a way for achieving these goals. We reasoned that "understanding PPO targeting and routing, designing ways to manipulate its expression and assessing the effects of such modifications will enable determination of the true properties of the enzyme and open the way for controlling its activity". The objective of the project was to "obtain an insight into the function and biological significance of PPOs" by examining possible function(s) of PPO in photosynthesis and plant-pest interactions using transgenic tomato plants; extending our understanding of PPO routing and assembly and the mechanism of its thylakoid translocation; preparing recombinant PPOs for use in import studies, determination of the genuine properties of PPOs and understanding its assembly and determining the effect of PPO's absence on chloroplast performance. Results obtained during work on the project made it necessary to abandon some minor objectives and devote the effort to more promising topics. Such changes are mentioned in the 'Body of the report' which is arranged according to the objectives of the original proposal. The complex expression pattern of tomato PPO gene family was determined. Individual members of the family are differentially expressed in various parts of the plant and subjected to developmentally regulated turnover. Some members are differentially regulated also by pathogens, wounding and chemical wound signals. Wounding systemically induces PPO activity and level in potato. Only tissues that are developmentally competent to express PPO are capable of responding to the systemic wounding signal by increased accumulation of PPO mRNA. Down regulation of PPO genes causes hyper susceptibility to leaf pathogens in tomato while over expression regulation of PPO expression in tomato plants is their apparent increased tolerance to drought. Both the enhanced disease resistance conferred by PPO over expression and the increased stress tolerance due to down regulation can be used in the engineering of improved crop plants. Photosynthesis rate and variable fluorescence measurements in wild type, and PPO-null and over expressing transgenic tomato lines suggest that PPO does not enable plants to cope better with stressful high light intensities or reactive oxygen species. Rather high levels of the enzyme aggravate the damage caused under such conditions. Our work suggests that PPO's primary role is in defending plants against pathogens and herbivores. Jasmonate and ethylene, and apparently also salicylate, signals involved in responses to wounding and defense against herbivores and pathogens, enhance markedly and specifically the competence of chloroplasts to import and process pPPO. The interaction of the precursor with thylakoid membranes is primarily affected. The routing of PPO shows other unusual properties: stromal processing occurs in two sites, resulting in intermediates that are translocated across thylakoids by two different mechanisms - a DpH- and a Sec-dependent one. It is suggested that the dual pattern of processing and routing constitutes a'fail safe' mechanism, reflecting the need for a rapid and flexible response to defense challenges. Many of the observations described above should be taken into consideration when manipulation of PPO expression is contemplated for use in crop improvement.
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Harben, P. E., D. Harris, S. Myers, S. Larsen, J. Wagoner, J. Trebes, and K. Nelson. Developing Smart Seismic Arrays: A Simulation Environment, Observational Database, and Advanced Signal Processing. Office of Scientific and Technical Information (OSTI), September 2003. http://dx.doi.org/10.2172/15005887.

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