Relevant bibliographies by topics / Signal fusion

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Signal fusion'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Signal fusion"

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Tejedor, Javier, Constantino A. García, David G. Márquez, Rafael Raya, and Abraham Otero. "Multiple Physiological Signals Fusion Techniques for Improving Heartbeat Detection: A Review." Sensors 19, no. 21 (October 29, 2019): 4708. http://dx.doi.org/10.3390/s19214708.

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This paper presents a review of the techniques found in the literature that aim to achieve a robust heartbeat detection from fusing multi-modal physiological signals (e.g., electrocardiogram (ECG), blood pressure (BP), artificial blood pressure (ABP), stroke volume (SV), photoplethysmogram (PPG), electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG), among others). Techniques typically employ ECG, BP, and ABP, of which usage has been shown to obtain the best performance under challenging conditions. SV, PPG, EMG, EEG, and EOG signals can help increase performance when included within the fusion. Filtering, signal normalization, and resampling are common preprocessing steps. Delay correction between the heartbeats obtained over some of the physiological signals must also be considered, and signal-quality assessment to retain the best signal/s must be considered as well. Fusion is usually accomplished by exploiting regularities in the RR intervals; by selecting the most promising signal for the detection at every moment; by a voting process; or by performing simultaneous detection and fusion using Bayesian techniques, hidden Markov models, or neural networks. Based on the results of the review, guidelines to facilitate future comparison of the performance of the different proposals are given and promising future lines of research are pointed out.
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Devaux, Philippe F. "Signal transduction during biomembrane fusion." Trends in Biochemical Sciences 19, no. 8 (August 1994): 346–47. http://dx.doi.org/10.1016/0968-0004(94)90077-9.

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Gomperts, B. D. "Signal transduction during biomembrane fusion." Trends in Cell Biology 4, no. 1 (January 1994): 31–32. http://dx.doi.org/10.1016/0962-8924(94)90039-6.

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Li, Lian Tian. "The Research on Abnormal Signal Retrieval Methods for Differences Equipments under the Framework of Large-Scale Internet of Things." Advanced Materials Research 846-847 (November 2013): 1060–63. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1060.

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This paper proposes an abnormal signal retrieval method for differences equipments in Internet of Things (IOT) based on Signal Fusion Technology. It elaborates on the fusion rules for communication signal of underlying devices, according to which describes the conditions need to be met when abnormal signal of the underlying devices in IOT is fused. Laplace energy and weighting algorithm are adopted to fuse abnormal signals of the underlying multi-device in IOT in order to achieve fusion detection for abnormal signal. Experimental results show that the algorithm can greatly improve the efficiency of detecting abnormal signal.
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Li, Wang, Shang Guan Wei, Bai Gen Cai, and Jian Wang. "Signal Simulation of the Train Integrated Positioning System." Advanced Materials Research 740 (August 2013): 86–91. http://dx.doi.org/10.4028/www.scientific.net/amr.740.86.

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In order to simulate the multi-sensor signals of the train integrated positioning system, and make signal fusion and verification, the train integrated positioning signal simulation system is introduced in this paper, which is based on GNSS and multi-sensor integrated positioning thoughts, the mathematical models and failure characteristics of the sensors are analyzed, the pulse speed sensor and gyro error models are established, the data simulation approach and data acquisition modules are adopted to simulate pulse speed sensor and gyroscope signals, the GNSS simulator is used to simulate GNSS signal under different scenes and conditions, signal fusion algorithms are used to conduct fusion and filtering of the integrated positioning signal. The results show the availability of the simulated signals. The train integrated positioning signal simulation system provides test environments with the parameters controllable, and lays a good foundation for the researches of the Beidou based integrated positioning system and the multi-mode satellite positioning technology.
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Liu, Wen Qiang, Gui Li Tao, Ze Yuan Gu, and Song Li. "Self-Tuning Weighted Measurement Fusion Kalman Signal Filter." Applied Mechanics and Materials 274 (January 2013): 579–82. http://dx.doi.org/10.4028/www.scientific.net/amm.274.579.

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For the single channel autoregressive moving average (ARMA) signals with multisensor and a colored measurement noise, when the model parameters and noise variances are partially unknown, based on identification method and Gevers-Wouters algorithm with a dead band, a self-tuning weighted measurement fusion Kalman signal filter is presented. A simulation example applied to signal processing shows its effectiveness.
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Jiang, Feng, Jun Yu, and Jian Jun Chen. "Design of Low Voltage Cell Fusion Instrument." Applied Mechanics and Materials 268-270 (December 2012): 1337–40. http://dx.doi.org/10.4028/www.scientific.net/amm.268-270.1337.

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Aimed at the deficiency in the existing cell-elctrofusion devices such as high fusion voltage and so on, a low voltage cell fusion system based on micro system technology is developed. This system is composed by cell fusion chip and low voltage signal generator, and locating cells by precisely designed microstructure and signal. In this chip, small distance between one pair of microelectrodes reduced required voltage. It has advantages of low energy consuming, small bulk and operation safety and easily compared with the existence apparatus. The experiment shows the system can generate cell fusion signal to meet the need for fusing. It can be popularized.
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Meng, Zong, Zuozhou Pan, Zijun Chen, and Ying Shi. "Adaptive signal fusion based on relative fluctuations of variable signals." Measurement 148 (December 2019): 106909. http://dx.doi.org/10.1016/j.measurement.2019.106909.

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Song, Qiang. "Data Fusion for MFL Signal Characterization." Applied Mechanics and Materials 44-47 (December 2010): 3519–23. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3519.

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The objective of data fusion is to be able to draw inferences that may not be feasible with data from a single sensor alone. In this paper, data from three sets of sensors are fused to estimate the defect profile from magnetic flux leakage (MFL) inspection data. The three sensors measure the axial, radial and tangential components of the MFL field. Data is fused at the feature level. Examples of signal features are amplitude, width, etc. A radial basis function network (RBFN) is then employed to map the fused features appropriately to obtain the geometric profile of the defect. The feasibility of the approach is evaluated using the data obtained from the MFL inspection of oil pipes. The results obtained by fusing the axial, radial and tangential components appear to be better than those obtained using the axial and radial component alone.
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Su, Liyun, Meini Li, Shengli Zhao, and Ting Xie. "Distributed Sensor Local Linear Fusion Detection of Weak Pulse Signal in Chaotic Background." Journal of Sensors 2021 (February 10, 2021): 1–11. http://dx.doi.org/10.1155/2021/6661142.

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This paper combines the distributed sensor fusion system with the signal detection under chaotic noise to realize the distributed sensor fusion detection from chaotic background. First, based on the short-term predictability of the chaotic signal and its sensitivity to small interference, the phase space reconstruction of the observation signal of each sensor is carried out. Second, the distributed sensor local linear autoregressive (DS-LLAR) model is constructed to obtain the one-step prediction error of each sensor. Then, we construct a Bayesian risk model and also obtain the corresponding conditional probability density function under each sensor’s hypothesis test which firstly needs to fit the distribution of prediction errors according to the parameter estimation. Finally, the fusion optimization algorithm is designed based on the Bayesian fusion criterion, and the optimal decision rule of each sensor and the optimal fusion rule of the fusion center are jointly solved to effectively detect the weak pulse signal in the observation signal. Simulation experiments show that the proposed method which used a distributed sensor combined with a local linear model can effectively detect weak pulse signals from chaotic background.
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Dissertations / Theses on the topic "Signal fusion"

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Zachariah, Dave. "Estimation for Sensor Fusion and Sparse Signal Processing." Doctoral thesis, KTH, Signalbehandling, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-121283.

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Progressive developments in computing and sensor technologies during the past decades have enabled the formulation of increasingly advanced problems in statistical inference and signal processing. The thesis is concerned with statistical estimation methods, and is divided into three parts with focus on two different areas: sensor fusion and sparse signal processing. The first part introduces the well-established Bayesian, Fisherian and least-squares estimation frameworks, and derives new estimators. Specifically, the Bayesian framework is applied in two different classes of estimation problems: scenarios in which (i) the signal covariances themselves are subject to uncertainties, and (ii) distance bounds are used as side information. Applications include localization, tracking and channel estimation. The second part is concerned with the extraction of useful information from multiple sensors by exploiting their joint properties. Two sensor configurations are considered here: (i) a monocular camera and an inertial measurement unit, and (ii) an array of passive receivers. New estimators are developed with applications that include inertial navigation, source localization and multiple waveform estimation. The third part is concerned with signals that have sparse representations. Two problems are considered: (i) spectral estimation of signals with power concentrated to a small number of frequencies,and (ii) estimation of sparse signals that are observed by few samples, including scenarios in which they are linearly underdetermined. New estimators are developed with applications that include spectral analysis, magnetic resonance imaging and array processing.

QC 20130426

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Reboul, Serge. "Estimation et détection conjointe pour la fusion d'informations." Habilitation à diriger des recherches, Université du Littoral Côte d'Opale, 2014. http://tel.archives-ouvertes.fr/tel-01067478.

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La détection des changements ou ruptures dans les paramètres de la distribution statistique d'une série temporelle est un problème de recherche en traitement du signal qui trouve des applications dans de nombreux domaines comme le traitement des signaux GNSS. Le projet scientifique développé dans mon mémoire d'habilitation à diriger des recherches concerne l'étude des méthodes d'estimation et de détection conjointe de ruptures pour la fusion d'informations. Les approches proposées dans ce cadre sont utilisées dans différentes applications comme l'estimation des paramètres du vecteur vent, le traitement des signaux GNSS et le filtrage des mesures fournies par les capteurs inertiels. L'objectif de la fusion est d'utiliser les informations ou mesures fournies par différents capteurs pour avoir une meilleure connaissance du paramètre à estimer. Nous avons donc proposé dans ce travail plusieurs méthodes d'estimation et de détection conjointe de rupture qui fusionnent les informations fournies par des capteurs. Le but étant d'améliorer les performances des opérateurs en termes de détection, de localisation et d'estimation de la dynamique des ruptures. Les approches proposées dans un cadre bayésien s'appuient sur la définition de la distribution a posteriori des paramètres à estimer sachant les mesures multi-capteurs. Un des apports de nos travaux dans ce domaine est de proposer un ensemble de filtres définis dans le domaine circulaire avec la distribution de von Mises. Un autre apport est de proposer une loi a priori qui modélise le comportement mutuel entre plusieurs processus dans le cas de la segmentation multi-ruptures hors ligne de signaux multi-capteurs. Ce travail a principalement été appliqué au géo positionnement et plus particulièrement au traitement de la phase et du code des signaux GNSS multi-porteuses. Nous avons montré par des expérimentations sur signaux réels que les méthodes proposées permettent d'obtenir une localisation centimétrique à la milliseconde d'un récepteur ayant un mouvement de forte dynamique. Aujourd'hui les perspectives de ce travail sont dans le traitement des signaux de réflectométrie GNSS et de géolocalisation sous-marine. En effet pour ces applications les signaux sont fortement atténués et déformés par le milieu de propagation, ce qui constitue un nouvel enjeu pour les méthodes de fusion d'informations en traitement du signal.
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Omar, Zaid Bin. "Signal processing algorithms for enhanced image fusion performance and assessment." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/10660.

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The dissertation presents several signal processing algorithms for image fusion in noisy multimodal conditions. It introduces a novel image fusion method which performs well for image sets heavily corrupted by noise. As opposed to current image fusion schemes, the method has no requirements for a priori knowledge of the noise component. The image is decomposed with Chebyshev polynomials (CP) being used as basis functions to perform fusion at feature level. The properties of CP, namely fast convergence and smooth approximation, renders it ideal for heuristic and indiscriminate denoising fusion tasks. Quantitative evaluation using objective fusion assessment methods show favourable performance of the proposed scheme compared to previous efforts on image fusion, notably in heavily corrupted images. The approach is further improved by incorporating the advantages of CP with a state-of-the-art fusion technique named independent component analysis (ICA), for joint-fusion processing based on region saliency. Whilst CP fusion is robust under severe noise conditions, it is prone to eliminating high frequency information of the images involved, thereby limiting image sharpness. Fusion using ICA, on the other hand, performs well in transferring edges and other salient features of the input images into the composite output. The combination of both methods, coupled with several mathematical morphological operations in an algorithm fusion framework, is considered a viable solution. Again, according to the quantitative metrics the results of our proposed approach are very encouraging as far as joint fusion and denoising are concerned. Another focus of this dissertation is on a novel metric for image fusion evaluation that is based on texture. The conservation of background textural details is considered important in many fusion applications as they help define the image depth and structure, which may prove crucial in many surveillance and remote sensing applications. Our work aims to evaluate the performance of image fusion algorithms based on their ability to retain textural details from the fusion process. This is done by utilising the gray-level co-occurrence matrix (GLCM) model to extract second-order statistical features for the derivation of an image textural measure, which is then used to replace the edge-based calculations in an objective-based fusion metric. Performance evaluation on established fusion methods verifies that the proposed metric is viable, especially for multimodal scenarios.
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Chikr, El-Mezouar Miloud. "Fusion d'images en télédétection satellitaire." Phd thesis, INSA de Rennes, 2012. http://tel.archives-ouvertes.fr/tel-00922646.

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Les satellites d'observation de la Terre fournissent des données multi-spectrales et panchromatiques ayant différentes résolutions spatiales, spectrales, temporelles, et radiométriques. La fusion d'une image panchromatique ayant une haute résolution spatiale, mais une basse résolution spectrale avec une image multi-spectrale ayant une basse résolution spatiale mais une haute résolution spectrale est très utile dans de nombreuses applications de télédétection nécessitant à la fois de hautes résolutions spatiales et spectrales. Dans l'image fusionnée les structures et les objets sont bien rehaussés et la classification de ces objets devient plus précise. Ces techniques de traitement d'image sont connues sous le nom de pansharpening ou techniques de fusion de résolutions. Dans cette thèse, trois algorithmes sont proposés pour la fusion dont deux dans la catégorie de substitution de composantes où nos principales contributions consistent à utiliser la transformée IHS et à rehausser la bande verte dans les zones de végétation. Dans le premier algorithme, la végétation est détectée en utilisant l'indice NDVI et le rehaussement de la végétation est effectué avant le processus de fusion. En revanche, pour le second algorithme le rehaussement de la végétation se fait après le processus de fusion et la végétation est délimitée à l'aide d'un nouvel indice (HRNDVI) proposé pour des images de hautes résolutions. HRNDVI est utilisé dans l'extraction de la végétation, même dans le cas complexe des zones urbaines où la végétation est dispersée. Ainsi, en utilisant HRNDVI, une nouvelle méthode a été proposée et testée pour extraire la végétation. Le troisième algorithme de pansharpening est inclus dans la catégorie multi-résolution basée sur la transformée NSCT. L'amélioration des résultats est assurée par l'utilisation d'un nombre de niveaux de décomposition réduit pour les images multi-spectrales et un nombre plus élevé de niveaux de décomposition pour l'image panchromatique. Cette stratégie permet d'aboutir à des résultats visuels et quantitatifs satisfaisants. En outre, la contribution de la thèse se trouve aussi dans l'évaluation de la qualité des images fusionnées. C'est ainsi qu'un nouveau protocole pour l'évaluation de la qualité est proposé. En fonction de l'application visée, il peut être réglé pour favoriser la qualité spectrale ou spatiale.
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Cavanaugh, Andrew F. "Bayesian Information Fusion for Precision Indoor Location." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/157.

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This thesis documents work which is part of the ongoing effort by the Worcester Polytechnic Institute (WPI) Precision Personnel Locator (PPL) project, to track and locate first responders in urban/indoor settings. Specifically, the project intends to produce a system which can accurately determine the floor that a person is on, as well as where on the floor that person is, with sub-meter accuracy. The system must be portable, rugged, fast to set up, and require no pre-installed infrastructure. Several recent advances have enabled us to get closer to meeting these goals: The development of Transactional Array Reconciliation Tomography(TART) algorithm, and corresponding locator hardware, as well as the integration of barometric sensors, and a new antenna deployment scheme. To fully utilize these new capabilities, a Bayesian Fusion algorithm has been designed. The goal of this thesis is to present the necessary methods for incorporating diverse sources of information, in a constructive manner, to improve the performance of the PPL system. While the conceptual methods presented within are meant to be general, the experimental results will focus on the fusion of barometric height estimates and RF data. These information sources will be processed with our existing Singular Value Array Reconciliation Tomography (σART), and the new TART algorithm, using a Bayesian Fusion algorithm to more accurately estimate indoor locations.
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Kota, Srinivas. "Dimensionality Reduction and Fusion Strategies for the Design of Parametric Signal Classifiers." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/171.

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This dissertation focuses on two specific problems related to the design of parametric signal classifiers: dimensionality reduction to overcome the curse of dimensionality and information fusion to improve classification by exploiting complementary information from multiple sensors or multiple classifiers. Dimensionality reduction is achieved by introducing a strategy to rank and select a subset of principal component transform (PCT) coefficients that carry the most useful discriminatory information. The criteria considered for ranking transform coefficients include magnitude, variance, inter-class separation, and classification accuracies of individual transform coefficients. The ranking strategy not only facilitates overcoming the dimensionality curse for multivariate classifier implementation but also provides a means to further select, out of a rank-ordered set, a smaller set of features that give the best classification accuracies. Because the class-conditional densities of transform feature vectors are often assumed to be multivariate Gaussian, the dimensionality reduction strategy focuses on overcoming the specific problems encountered in the design of practical multivariate Gaussian classifiers using transform feature vectors. Through experiments with event related potentials (ERPs) and ear pressure signals, it is shown that the dimension of the feature space can be decreased quite significantly by means of the feature ranking and selection strategy. Furthermore, the resulting Gaussian classifiers yield higher classification accuracies than those reported in previous classification studies on the same signal sets. Amongst the four feature selection criteria, Gaussian classifiers using the maximum magnitude and maximum variance selection criteria gave the best classification accuracies across the two sets of classification experiments. For the multisensor case, dimensionality reduction is achieved by introducing a spatio-temporal array model to observe the signals across channels and time, simultaneously. A two-step process which uses the Kolmogrov-Smirnov test and the Lilliefors test is formulated to select the array elements which have different Gaussian densities across all signal categories. Selecting spatio-temporal elements that fit the assumed model and also statistically differ across the signal categories not only decreases the dimensionality significantly but also ensures high classification accuracies. The selection is dynamic in the sense that selecting spatio-temporal array elements corresponds to selecting samples of different sensors at different time-instants. Each selected array element is classified using a univariate Gaussian classifier and the resulting decisions are fused into a decision fusion vector which is classified using a discrete Bayes classifier. The application of the resulting dynamic channel selection-based classification strategy is demonstrated by designing and testing classifiers for multi-channel ERPs and it is shown that strategy yields high classification accuracies. Most noteworthy of the two dimensionality reduction strategies is the fact that the multivariate Gaussian signal classifiers developed can be implemented without having to collect a prohibitively large number of training signals simply to satisfy the dimensionality conditions. Consequently, the classification strategies can be beneficial for designing personalized human-machine-interface (HMI) signal classifiers for individuals from whom only a limited number of training signals can reliably be collected due to severe disabilities. The information fusion strategy introduced is aimed at improving the performance of signal classifiers by combining signals from multiple sensors or by combining decisions of multiple classifiers. Fusion classifiers with diverse components (classifiers or data sets) outperform those with less diverse components. Determining component diversity, therefore, is of the utmost importance in the design of fusion classifiers which are often employed in clinical diagnostic and numerous other pattern recognition problems. A new pairwise diversity-based ranking strategy is introduced to select a subset of ensemble components, which when combined, will be more diverse than any other component subset of the same size. The strategy is unified in the sense that the components can be either polychotomous classifiers or polychotomous data sets. Classifier fusion and data fusion systems are formulated based on the diversity selection strategy and the application of the two fusion strategies are demonstrated through the classification of multi-channel ERPs. From the results it is concluded that data fusion outperforms classifier fusion. It is also shown that the diversity-based data fusion system outperforms the system using randomly selected data components. Furthermore, it is demonstrated that the combination of data components that yield the best performance, in a relative sense, can be determined through the diversity selection strategy.
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Steen, Preston S. T. "The application of connectionist models to radar signal recognition and fusion." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240109.

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Saleem, Amina. "Image enhancement using a perceptual fusion approach." Paris 13, 2012. http://scbd-sto.univ-paris13.fr/intranet/edgalilee_th_2012_saleem.pdf.

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Due to limitations in image acquisition and transmission systems, image enhancement is established as an important area in image processing. Removing noise and blur, improving contrast to reveal details, coding artifact reduction and luminance adjustment are some image processing tasks that fall in the broader category of image enhancement operations. The problem of image enhancement is not a trivial task, since each image has its own characteristics and different image applications demand different enhancement requirements. It is therefore, hard to find a universal enhancement technique that would satisfy such diverse requirements. This justifies the presence of number of enhancement methods and ongoing research to find methods that can achieve different enhancement goals at the same time. Generally, image enhancement algorithms are developed to achieve some attributes of enhancement at the expense of some others. In our thesis, we develop a framework for fusion based image enhancement which is presented as a solution to the deficiencies of image enhancement algorithms. Fusion based methods for contrast enhancement, multi-focus image fusion and deblocking are developed with applications to tone mapping for HDR and natural enhancement of color images
La qualité de l’image perceptuelle depend essentiellement des conditions d’observation et d’acquisition, et les limitations des systems de numérisation et de transmission. On a souvent recours aux méthodes de restauration d’image et de réduction des artéfacts générés durant l’acquisition, le codage ou la transmission. Cependant, l’amélioration de la qualité d’image est un problème difficile en soi en raison de l’absence de critères objectifs bien établis pour juger des résultats. En effet, la qualité d’image est avant tout une notion subjective qui dépend de plusieurs paramètres psycho-visuels incontrôlables. De plus, chaque image a ses propres charactéristiques, et les solutions proposées dépendent aussi des applications visées. Par exemple, le réhaussement de contraste peut s’avérer efficace dans certaines zones de l’image, mais néfaste dans d’autres. Il est donc difficile de trouver une technique d’amélioration universelle qui puisse satisfaire les diverses exigences inhérentes au signal d’image. L’objectif de ce travail est de développer des méthodes basées sur une nouvelle approche où l’on fait appel à la fusion d’information et la modélisation des mécanismes de la perception visuelle. Dans ce cadre, nous proposons des méthodes de réhaussement de contraste, de filtrage et de bruit, de réductions des artefacts de codage et d’ajustement et d’équilibrage de tonalité chromatique dans le cas d’images, « HDRI ». Les performances des méthodes développées peuvent pallier les limitations des solutions de l’état de l’art et ouvrent ainsi de grandes perspectives
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Abyarjoo, Fatemeh. "Sensor Fusion for Effective Hand Motion Detection." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2215.

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Meline, Arnaud. "Fusion multimodale pour la cartographie sous-marine." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2013. http://tel.archives-ouvertes.fr/tel-01054546.

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Le but de ce travail est d'analyser des scènes sous-marines naturelles et en particulier cartographier des environnements sous-marins en 3D. Il existe aujourd'hui de nombreuses techniques pour résoudre ce problème. L'originalité de ce travail se trouve dans la fusion de deux cartes obtenues avec des capteurs de différentes résolutions.Dans un premier temps, un engin autonome (ou un bateau) analyse les fonds marins avec un sonar multifaisceaux et crée une première carte globale de la zone. Cette carte est ensuite décomposée en petites cellules représentant une mosaïque du fond marin. Une deuxième analyse est ensuite réalisée sur certaines cellules particulières à l'aide d'un second capteur avec une résolution plus élevée. Cela permettra d'obtenir une carte détaillée 3D de la cellule. Un véhicule autonome sous-marin ou un plongeur muni d'un système de vision stéréoscopique effectuera cette acquisition. Ce projet se décompose en deux parties, la première s'intéressera à la reconstruction 3D de scènes sous-marines en milieu contraint à l'aide d'une paire stéréoscopique. La deuxième partie de l'étude portera sur l'aspect multimodal. Dans notre cas, nous utilisons cette méthode pour obtenir des reconstructions précises d'objets d'intérêts archéologiques (statues, amphores, etc.) détectés sur la carte globale. La première partie du travail concerne la reconstruction3D de la scène sous-marine.Même si aujourd'hui le monde de la vision a permis de mieux appréhender ce type d'image, l'étude de scène sous-marine naturelle pose encore de nombreux problèmes. Nous avons pris en compte les bruits sous-marins lors de la création du modèle 3D vidéo ainsi que lors de la calibration des appareils photos. Une étude de robustesse à ces bruits a été réalisée sur deux méthodes de détections et d'appariements de points d'intérêt. Cela a permis d'obtenir des points caractéristiques précis et robustes pour le modèle 3D. La géométrie épipolaire nous a permis de projeter ces points en 3D. La texture a été ajoutée sur les surfaces obtenues par triangulation de Delaunay. La deuxième partie consiste à fusionner le modèle 3D obtenu précédemment et la carte acoustique. Dans un premier temps, afin d'aligner les deux modèles 3D (le modèle vidéo et le modèle acoustique), nous appliquons un recalage approximatif en sélectionnant manuellement quelques paires de points équivalents sur les deux nuages de points. Pour augmenter la précision de ce dernier, nous utilisons un algorithme ICP (Iterative Closest Points). Dans ce travail nous avons créé une carte 3D sous-marine multimodale réalisée à l'aide de modèles 3D " vidéo " et d'une carte acoustique globale.
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Books on the topic "Signal fusion"

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Bloch, Isabelle, ed. Information Fusion in Signal and Image Processing. London, UK: ISTE, 2008. http://dx.doi.org/10.1002/9780470611074.

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Goodman, I. R. Mathematics of Data Fusion. Dordrecht: Springer Netherlands, 1997.

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Martin, Golz, Kuh Anthony, Obradovic Dragan, Tanaka Toshihisa, and SpringerLink (Online service), eds. Signal Processing Techniques for Knowledge Extraction and Information Fusion. Boston, MA: Springer Science+Business Media, LLC, 2008.

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Mandic, Danilo, Martin Golz, Anthony Kuh, Dragan Obradovic, and Toshihisa Tanaka, eds. Signal Processing Techniques for Knowledge Extraction and Information Fusion. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7.

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L, Hall David. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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Hall, David L. Mathematical techniques in multisensor data fusion. Boston: Artech House, 1992.

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Sensor array signal processing. Boca Raton, FL: CRC Press, 2001.

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L, Hall David. Mathematical techniques in multi-sensor data fusion. 2nd ed. Boston: Artech House, 2004.

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Varshney, Pramod K. Distributed detection and data fusion. Edited by Burrus C. S. New York: Springer, 1997.

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Varshney, Pramod K. Distributed detection and data fusion. Edited by Burrus C. S. Berlin: Springer, 1996.

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Book chapters on the topic "Signal fusion"

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Zimmermann, Armin. "Multi-Sensory Signal Fusion." In Analysis and Control of Industrial Processes, 232–44. Wiesbaden: Vieweg+Teubner Verlag, 1991. http://dx.doi.org/10.1007/978-3-322-88847-1_19.

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Tykocinski, Mark L. "Signal Converter Proteins." In Fusion Protein Technologies for Biopharmaceuticals, 453–73. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118354599.ch30.

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Li, Ye, Li Xu, Ya Gang Wang, and Xiao Ming Xu. "A New Diversity Measure for Classifier Fusion." In Multimedia and Signal Processing, 396–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_50.

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Luo, Xiaoqing, Xiaojun Wu, and Zhancheng Zhang. "A Novel Framework about Multi-focus Image Fusion." In Multimedia and Signal Processing, 32–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_5.

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Fasil, O. K., R. Rajesh, and T. M. Thasleema. "Fusion of Signal and Differential Signal Domain Features for Epilepsy Identification in Electroencephalogram Signals." In Advances in Data and Information Sciences, 127–35. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8360-0_12.

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Chen, Yong, Zhi-Ming Wang, and Hong Bao. "Multi-phase Fusion of Visible-Infrared Information for Motion Detection." In Multimedia and Signal Processing, 325–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_41.

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Devagiri, Rohini, Nalini C. Iyer, and Shruti Maralappanavar. "Real-time RADAR and LIDAR Sensor Fusion for Automated Driving." In Machine Intelligence and Signal Processing, 137–47. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1366-4_11.

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Su, Zhongqing, and Lin Ye. "Algorithms for Damage Identification – Fusion of Signal Features." In Identification of Damage Using Lamb Waves, 195–254. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-784-4_6.

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Zhang, Peng, and Zili Deng. "Multichannel ARMA Signal Covariance Intersection Fusion Kalman Filter." In 2011 International Conference in Electrics, Communication and Automatic Control Proceedings, 181–87. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8849-2_23.

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Barra, Silvio, Andrea Casanova, Matteo Fraschini, and Michele Nappi. "EEG/ECG Signal Fusion Aimed at Biometric Recognition." In New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops, 35–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23222-5_5.

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Conference papers on the topic "Signal fusion"

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Sun, Ming-Ting. "Multimodal signal fusion." In 2009 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2009. http://dx.doi.org/10.1109/icme.2009.5202805.

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Mertens, M., and M. Ulmke. "GMTI tracking using signal strength information." In 2010 13th International Conference on Information Fusion (FUSION 2010). IEEE, 2010. http://dx.doi.org/10.1109/icif.2010.5712062.

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Chen, Chen, Mengjiao Tang, Jie Zhou, and Yao Rong. "Signal Detection with Elliptically Distributed Observations in Sensor Arrays." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455215.

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Cao, Lingxiao, Guolong Cui, Lingjiang Kong, Shisheng Guo, Huquan Li, and Guohao Chen. "Narrow-Band Through-Wall Imaging with Received Signal Strength Data." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455473.

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Wang, Qi, Zhansheng Duan, X. Rong Li, and Uwe D. Hanebeck. "Convex Combination for Source Localization Using Received Signal Strength Measurements." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455659.

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Satar, Baris, Yetkin Ersoy, Gokhan Soysal, and Murat Efe. "A do it Yourself Mobile Communications Signal Based Passive Radar." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455848.

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Ye, Fan, Feng He, and Zaoyu Sun. "Radar Signal Level Fusion Imaging." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779966.

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Chen, Tao, Badong Chen, Wentao Ma, and Lei Sun. "Quaternion least mean kurtosis algorithm for adaptive filtering of 3D and 4D signal processes." In 2017 20th International Conference on Information Fusion (Fusion). IEEE, 2017. http://dx.doi.org/10.23919/icif.2017.8009739.

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Ahmad, Bashar I., Tohid Ardeshiri, Pat Langdon, Simon J. Godsill, and Thomas Popham. "Modelling received signal strength from on-vehicle BLE beacons using skewed distributions: A preliminary study." In 2017 20th International Conference on Information Fusion (Fusion). IEEE, 2017. http://dx.doi.org/10.23919/icif.2017.8009763.

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Khanduri, Prashant, Lakshmi Narasimhan Theagarajan, and Pramod K. Varshney. "Online Design of Precoders for High Dimensional Signal Detection in Wireless Sensor Networks." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455834.

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Reports on the topic "Signal fusion"

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Jassby, D. L. Application of small-signal fusion energy gain. Office of Scientific and Technical Information (OSTI), November 1986. http://dx.doi.org/10.2172/6986172.

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Blum, Rick S. A Theory for Distributed Signal Detection and Data Fusion. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada377472.

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Brady, David J., James J. Coleman, and Kenneth G. Purchase. Ultra-Fast Optical Signal Encoding and Analysis for Communications and Data Fusion Networks. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada377846.

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Ramchandran, Kannan, and Kristofer Pister. Sensor Webs of SmartDust: Distributed Signal Processing/Data Fusion/Inferencing in Large Microsensor Arrays. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada422190.

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Chau, Yawgeng A., and Evaggelos Geraniotis. Optimal Quantization and Fusion in Multi-Sensor Systems for the Detection of Weak Signals in Dependent Noise. Fort Belvoir, VA: Defense Technical Information Center, January 1989. http://dx.doi.org/10.21236/ada454791.

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Vargas-Herrera, Hernando, Pamela Andrea Cardozo-Ortiz, Clara Lía Machado-Franco, Carlos Alberto Cadena-Silva, Freddy Hernán Cepeda-López, Aura María Ciceri-Lozano, Carlos Eduardo León-Rincón, et al. Reporte de Sistemas de Pago - Junio de 2021. Banco de la República de Colombia, July 2021. http://dx.doi.org/10.32468/rept-sist-pag.2021.

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Abstract:
El Banco de la República, con el Reporte de Sistemas de Pago, entrega un panorama completo de la infraestructura financiera local, siendo este un producto importante de la labor de seguimiento a dicha infraestructura. Las cifras contenidas en este reporte corresponden al año 2020, período de pandemia durante el cual las medidas de confinamiento para aliviar la tensión sobre el sistema de salud generaron para Colombia, al igual que en la mayoría de los países, una fuerte reducción de la actividad económica y el consumo. Desde el comienzo de la pandemia, la Junta Directiva del Banco de la República adoptó las decisiones necesarias para otorgar al mercado amplia liquidez en pesos y dólares, garantizar la estabilidad de los mercados, proteger el sistema de pagos y preservar la oferta de crédito. El pronunciado crecimiento de los agregados monetarios reflejó la mayor preferencia por liquidez, la cual fue atendida oportunamente por el Banco de la República. Las decisiones adoptadas se realizaron mediante diferentes operaciones, las cuales fueron compensadas y liquidadas en la infraestructura financiera. Después de la introducción, la segunda sección del presente reporte de pagos analiza la evolución y el desempeño de las diferentes infraestructuras financieras. Se destaca que el sistema de pagos de alto valor CUD registró en 2020 un mayor dinamismo que el año anterior, principalmente por el aumento de los depósitos remunerados que en promedio diario realizó la Dirección General de Crédito Público y del Tesoro Nacional (DGCPTN) con el Banco de República, así como una mayor actividad del mercado de simultáneas de deuda pública. Consecuentemente con el crecimiento de la actividad en el CUD, el Depósito Central de Valores (DCV) registró una mayor actividad por el aumento del mercado monetario de deuda pública y por las colocaciones por parte del Gobierno Nacional en el mercado primario. El valor de las operaciones compensadas y liquidadas por intermedio de la Cámara de Riesgo Central de Contraparte (CRCC) continúa creciendo, jalonado principalmente por los contratos non delivery forward (NDF) peso/dólar. Con respecto a la CRCC, es oportuno mencionar que a partir de finales del año pasado esta cámara se encarga de administrar los riesgos y de compensar y liquidar las operaciones del mercado de contado peso/dólar, debido a la fusión con la Cámara de Compensación de Divisas de Colombia (CCDC). Así mismo, a partir del último trimestre del año 2020 la CRCC se encarga de compensar y liquidar el mercado de renta variable, labor que venía desempeñando la Bolsa de Valores de Colombia (BVC). En la sección tres se entrega una visión integral de los pagos en el mercado de bienes y servicios, es decir, de las transacciones efectuadas en el circuito de personas naturales y empresas no financieras. Durante la pandemia las transferencias electrónicas inter e intrabancarias, que en su mayoría son originadas por empresas, registraron un incremento tanto en número como en valor de operaciones frente a 2019. Por su parte, los pagos con tarjetas débito y crédito originados principalmente por personas naturales mostraron un comportamiento decreciente con respecto a 2019. Los pagos realizados con cheques siguen disminuyendo, presentando una tendencia a la baja muy pronunciada en el último año. Como complemento a la información sobre transferencias electrónicas, el reporte incluye en esta sección un sombreado sobre la caracterización de la población con cuenta de ahorro y corriente, empleando los datos de la encuesta del Banco de la República sobre percepción de uso de los instrumentos de pago en 2019. Se incluye también un recuadro sobre la evolución transaccional de una billetera móvil provista por una sociedad especializada en depósitos y pagos electrónicos (Sedpe), mostrando que desde su creación a finales del año 2017 ha incremento en el número de usuarios y el valor de las transacciones, con especial velocidad durante la pandemia. Adicionalmente, se presenta un diagnóstico sobre los efectos de la pandemia en los patrones de pago de la población, fundamentado en datos sobre el uso del efectivo en circulación, sobre los pagos con instrumentos electrónicos, y sobre el consumo y la confianza del consumidor. Se concluye que el desplome en el índice de confianza del consumidor y la caída en el consumo privado dieron lugar a cambios en los patrones de pago de las personas. Las compras con tarjetas de crédito y débito disminuyeron, mientras que los pagos por bienes y servicios mediante transferencia electrónica aumentaron. Estos resultados, junto con el considerable aumento del efectivo en circulación, podrían proveer indicios a favor de un posible atesoramiento del papel moneda con motivo precaución por parte de las personas y de un mayor uso del efectivo como instrumento de pago. Se incluye, además, un recuadro que presenta los principales cambios que se introdujeron en la regulación del sistema de pagos de bajo valor en el país mediante la expedición del Decreto 1692 de diciembre de 2020. La cuarta sección se refiere a las importantes innovaciones y cambios tecnológicos que se han observado en el sistema de pagos al por menor. Se destacan cuatro temas en esta línea. El primero se constituye en un punto clave para la construcción de la infraestructura financiera de pagos inmediatos. Consiste en el diseño e implementación de los llamados esquemas superpuestos, los cuales son un desarrollo tecnológico que permite una comunicación abierta entre los diferentes agentes de la cadena de pagos, logrando una alta interoperabilidad entre diferentes proveedores de servicios de pago. El segundo tema explora los avances en el debate internacional sobre la emisión de moneda digital por parte de los bancos centrales (CBDC por su sigla en inglés), con el fin de entender su posible impacto en el sistema de pagos de bajo valor y en el uso del efectivo. El tercer tema está relacionado con nuevas formas de iniciación de pagos, tales como los códigos QR, la biometría o la tecnología de comunicación de campos cercanos (NCF por su sigla en inglés). Estos cambios, aparentemente pequeños, pueden tener efectos importantes en la experiencia del usuario con el sistema de pagos de bajo valor. El cuarto tema, finalmente, es el crecimiento de los pagos vinculados con la telefonía móvil y el internet. El reporte finaliza en la sección cinco con una reseña de dos trabajos de investigación aplicada realizados en el Banco de la República en el año 2020. El primero analiza el nivel patrimonial de la CRCC, reconociendo el rol relevante que esta infraestructura ha adquirido en la compensación y liquidación de varios mercados financieros en el país. Se exploran los requerimientos de capital para las entidades de contrapartida central establecidos en algunas jurisdicciones, se identifican los riesgos que se busca cubrir desde la perspectiva del servicio que este tipo de entidades ofrece al mercado y aquellos asociados a su actividad corporativa. Se analizan los niveles patrimoniales de la CRCC a partir de lo observado en la regulación de la Unión Europea y se concluye que la CRCC cuenta con un esquema de anillos de seguridad muy similar al observado en la experiencia internacional y que su nivel patrimonial es superior al exigido por la regulación colombiana, siendo suficiente para cubrir otros riesgos. El segundo trabajo de investigación identifica y cuantifica las fuentes que utilizan las entidades participantes en el CUD para cumplir con sus obligaciones diarias contraídas en el mercado financiero local, y con su uso como herramienta de monitoreo de la liquidez intradía en condiciones normales. Leonardo Villar Gómez Gerente General
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