Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. The state space approach is then extended to discuss direct and indirect seasonal adjustments. This is achieved by applying a seasonal level model with no trend and some specific input variances that render different signal-to-noise ratios. This is illustrated for a system consisting of two artificial time series. Relative efficiencies between direct, indirect and multivariate, i.e. optimal, variances are then analyzed. In practice, standard seasonal adjustment packages do not support optimal/multivariate seasonal adjustments, so a univariate approach to simultaneous estimation is presented by specifying a Holt-Winters exponential smoothing method. This is applied to two sets of time series systems by defining a total loss function that is specified with a trade-off weight between the individual series’ loss functions and their aggregate loss function. The loss function is based on either the more conventional squared errors loss or on a robust Huber loss. The exponential decay parameters are then estimated by minimizing the total loss function for different trade-off weights. It is then concluded what approach, direct or indirect seasonal adjustment, is to be preferred for the two time series systems. The dynamic linear modeling approach is also applied to Swedish political opinion polls to assert the true underlying political opinion when there are several polls, with potential design effects and bias, observed at non-equidistant time points. A Wiener process model is used to model the change in the proportion of voters supporting either a specific party or a party block. Similar to stock market models, all available (political) information is assumed to be capitalized in the poll results and is incorporated in the model by assimilating opinion poll results with the model through Bayesian updating of the posterior distribution. Based on the results, we are able to assess the true underlying voter proportion and additionally predict the elections. / <p>At the time of doctoral defence the following papers were unpublished and had a status as follows: Paper 3: Manuscript; Paper 4: Manuscripts</p>

The theoretical part deals with a complex problematics of venous port systems, its history, indications.. The empirical part focuses on the knowledge of the nursing staff and their attitude towards their own skills in this area and also the majority of this part deals with client´s awareness and their experience. In order to elaborate this thesis a combination of quantity quality examination has been chosen. To realize a quantity research we selected a survey based technique and for the quality one we used a semi-structured conversation system with open questions. There was a survey assorted for a quantity research which was destined for the general nurses working at the surgical and intern departments within Southern Bohemia region. The quality research was conducted by 9 interviews with clients with the ports implanted. There were four goals being focused on in the thesis. The first one was to chart the nurses´ awareness regarding the port problematics. From the results came clear that the nurses don´t have the corresponding knowledge. The second focus was to find out the own attitude of the nurses towards their skills regarding the port care. The results proved that the nurses assess their skills mostly like insufficient. The third focus was trying to estimate the clients´ awareness about ports and their appreciation of nursing care. By means of these clients´ interviews we found out that they are well informed about the problematics and their care appreciation with ports is excellent. The fourth focus was searching for particular clients´ needs regarding their ports and their saturation by the nursing staff. From the clients´ responses were we able to find out that they don´t have. H1 The general nurses working at the surgical departments treat the clients with ports more often than those from the intern departments. It also shows that both nurses from surgical and internal departments meet the clients with ports equally. The first hypothesis has not been proved. H2 The general nurses working at the surgical departments have more knowledge about nursing clients with ports than those from the intern departments. The analysis has shown that nurses from intern departments have more knowledge than those from the surgical ones. The second hypothesis has not been proved. H3 The general nurses working at the surgical departments assess their skills regarding the care of client with implanted port better than those from intern departments. Nurses from both departments assess their skills mostly as insufficient. The third hypothesis has not been proved. H4 General nurses are interested in increasing their knowledge about the port problematics. The nurses proved interest about increasing their knowledge, e. g. by attending a special course. The fourth hypothesis has not been proved.Survey questionnaire: VO1 Do the clients have enough information about the ports? VO2 Does the port obstruct your daily activities? VO3 How is the port being estimated by the clients? VO4 What pros and cons have the ports from their point of view? VO5 How do the clients assess the nursing care? VO6 What particular needs do the clients with ports have? VO7 Are these needs saturated by the nursing staff? The survey research proved that the clients are satisfied with the ports. The care of ports is assessed perfectly by clients and it attests that the provided medical care is superior. Despite all those positive outcomes it´s essential that the nurses from oncology but also from other departments are being further educated in the port problematics as the results of quantity research points to a lack of knowledge of nurses and the number of clients with ports is increasing.The thesis can be used as an information source for nurses and management. We recommend regular education seminars and creation of nursing standards.

Les symptômes de base (Huber, 1957), aussi nommés plaintes cognitives par Cuesta, Peralta et Juan (1996), réfèrent à un groupe de symptômes moins connus mais dont l'intérêt s'est ravivé ces dernières années. Il s'agit de symptômes qui concernent spécifiquement le vécu expérientiel des personnes atteintes de schizophrénie et pouvant être qualifiés de perturbations subjectives. Ils se basent principalement sur le ressenti et non sur les altérations comportementales observables qui pourraient en découler. Une des premières échelles créées et la plus fréquemment utilisée pour mesurer les perturbations subjectives est le Questionnaire des plaintes de Francfort (QPF), élaboré par Sûllwold (1986). Le but de la présente thèse est d'explorer l'hypothèse de Huber à propos des perturbations subjectives telles que mesurées à l'aide du QPF. Selon Huber, ces perturbations constituent une partie essentielle des symptômes prodromiques et résiduels de la schizophrénie et elles seraient liées à la défaillance d'un processus élémentaire impliqué dans le filtrage de l'information. Dans cette optique, trois objectifs sont visés: 1. Examiner la structure factorielle du Questionnaire des plaintes de Francfort (QPF) ; 2. Étudier la relation entre les perturbations subjectives et la défaillance de certaines fonctions cognitives dans la schizophrénie ; 3. Étudier la relation entre les perturbations subjectives et d'autres catégories de symptômes de la schizophrénie. Les trois objectifs visés sont abordés comme des thèmes distincts qui se présentent sous la forme de trois articles. Sauf pour le premier article où la dimension statistique est au premier plan, c'est dans une approche de psychopathologie cognitive que se situent nos travaux. Ainsi, il s'agit d'expliquer une dimension symptomatologique de la schizophrénie (les perturbations subjectives) à partir du dysfonctionnement d'un processus élémentaire (Hardy-Bayle, 1997). L'article no 2 consiste en une étude corrélationnelle entre les perturbations subjectives et les fonctions cognitives d'inhibition et d'attention sélective. Quant à l'article no 3, il étudie la relation entre les perturbations subjectives et certaines dimensions symptomatologiques dont les symptômes positifs, négatifs et de psychopathologie générale. Suite aux articles, une discussion générale propose une synthèse et des perspectives de recherche.

Cities generally need economic growth. Green policies and projects are environmentally beneficial, desirable, expected by the public, and pragmatic in the long term. However, there is insufficient research on what, if any, municipal green projects and policies generate economic growth. To address this question, the author created a database of green and economic indicators, and modeled the green indicators to predict the economic indicators. The database included carbon usage, transportation metrics, water usage, the number of green jobs, and the gross domestic product (GDP) for the 100 largest cities, defined by metropolitan statistical area (MSA), in the U.S. To gather data on green indicators, existing green rankings, indices, and reports were evaluated for methodology and usability for this paper. The results of the data-gathering step show the need for more and better data collection. That means an increased number of green indicators should be collected, and data should be collected at the MSA (or county) level for more of the largest cities. Specifically to name some green indicators, data collection on energy usage, buildings, waste, land use, air quality, and food could be improved. Those green indicators would likely be included in a model that uses green indicators to predict green jobs or GDP. However, those were not included for the regressions in this paper. The results of the regressions in this paper show two indicators with promise for predicting economic growth as defined by GDP and number of green jobs: (1) percent of people using public transportation, biking, or walking to work, and (2) public water consumption per person. The first explanatory variable indirectly measures the adoption of policies that promote public transportation, biking, and walking. The results suggest that these policies have a positive effect on GDP and number of green jobs. This means the results suggest that as the percent increases, so does GDP and number of green jobs. The second explanatory variable measures the water conservation policies. The results suggest this variable has a negative, albeit weaker relationship with GDP per person. This means the results suggest as water conservation increases (less water usage per person), the GDP per person increases. This paper offers a methodology and some of the groundwork for building a model to show which, if any, municipal green projects and policies predict economic growth. / text

The aim of this work was to evaluate the physiological, growing and biochemical parameters of young plants of (Schizolobium amazonicum Huber ex Ducke) when submitted in diferente dosages of cadmium. The experimente was developed in greenhouse of Instituto de Ciências Agrárias (ICA), belonging to Universidade Federal Rural da Amazônia (UFRA), located in Belém-Pará, in a period of december 2017 to june 2018. Initially seedlings were produced from paricá seeds from Associação das Indústrias Exportadoras de Madeira do Estado do Pará in Benevides-Pará. The seeds were seeded in a Leonard type pot with a capacity of 4.6 L adapted with pet bottles containing washed and sterilized sand. After 15 days after sowing, they received nutritive solution of Sarruge (1/4 and 1/2 strength). After 60 days after sowing the application of increasing concentrations of cadmium in the form of cadmium chloride (CdCl2.H2O). Was utiized a randomized experimental design (RED), with 5 treatments being constituted of control plants (without cadmium dosages) and with cádmium dosages(CdCl2 178μM, CdCl2 356 μM, CdCl2 534μM, CdCl2 712 μM) with 7 repetitions each (one plant per pot) totalizing 35 experimental units. The obtained data were submitted to variance analysis by F test (p < 0,05) and the means were compared by the least significant difference of the Tukey's test (p<0,05) and were adjusted by polynomial regression equations P <0.01 or 0.05 using the Sisvar program. The mainly physiological variables (photosynthesis, stomatal conductance and transpiration) destabilized in their functions with the increase of the cadmium doses, influencing in the energy process of the same ones. The growth, diameter, leaf number and leaflet variables, cadmium provided a reduction as the doses were increased, interfering in the production of foliar biomass. Changes in physiological effects have consequently led to changes in plant metabolism and nitrogen, evidencing the low concentrations of nitrogen-containing molecules in their structures such as amino acids, proline, and glycine. The cadmium accumulated in the roots, but there was a translation for the aerial part. Given this, it can be corresponded as a phytoextractor. / O objetivo deste trabalho foi avaliar os parâmetros fisiológicos, de crescimento e bioquímicos de plantas jovens da espécie (Schizolobium amazonicum Huber ex Ducke) quando submetidas em diferentes concentrações de cádmio. O experimento foi desenvolvido em casa de vegetação do Instituto de Ciências Agrárias (ICA), pertencente a Universidade Federal Rural da Amazônia (UFRA), localizado em Belém-Pará, no período de dezembro de 2017 a junho de 2018. Inicialmente foram produzidas mudas a partir de sementes de paricá oriundas da Associação das Indústrias Exportadoras de Madeira do Estado do Pará em Benevides-Pará. As sementes foram semeadas em vaso tipo Leoanard com capacidade de 4,6 L adaptados com garrafas pet contendo areia lavada e esterilizada (120 ºC por 40 min.) Decorridos 15 dias após o semeio as mesmas receberam solução nutritiva de Sarruge. Transcorridos 60 dias após o semeio foi iniciada a aplicação das concentrações de cádmio na forma de cloreto de cádmio hidratado (CdCl2.H2O). Foi utilizado o delineamento experimental inteiramente casualizado (DIC), com 5 tratamentos sendo constituídos de plantas controle (sem cádmio) e com doses de Cádmio (CdCl2 178μM, CdCl2 356 μM, CdCl2 534μM, CdCl2 712 μM) Os dados foram submetidos análise de variância pelo teste F (p < 0,05) e as diferenças entre os tratamentos analisadas pelo teste de Tukey (p<0,05) e foram ajustadas por equações de regressão polinomial P<0,01 ou 0,05 usando-se o programa Sisvar. As principais variáveis fisiológicas (fotossíntese, condutância estomática e transpiração) desestabilizaram-se em suas funções com o aumento das doses de cádmio, influenciando no processo energético das mesmas. Para as variáveis de crescimento (altura, diâmetro, número de folhas e folíolos), o cádmio proporcionou uma diminuição à medida que as doses eram aumentadas, interferindo em menor produção de biomassa foliar. As alterações dos parâmetros fisiológicos, consequentemente levaram a mudanças no metabolismo do carbono e nitrogênio dessas plantas, evidenciando baixas concentrações das variáveis que contem nitrogênio em suas estruturas como aminoácidos, prolina, glicina. O cádmio acumulou-se principalmente nas raízes, mas porém houve translocação para parte aérea. Diante disso, pode-se caracteriza-lá como fitoextratora.

L'identification des systèmes dynamiques complexes reste une préoccupation lorsque les erreurs de prédictions contiennent des outliers d'innovation. Ils ont pour effet de détériorer le modèle estimé, si le critère d'estimation est mal choisi et mal adapté. Cela a pour conséquences de contaminer la distribution de ces erreurs, laquelle présente des queues épaisses et s'écarte de la distribution normale. Pour résoudre ce problème, il existe une classe d'estimateurs, dits robustes, moins sensibles aux outliers, qui traitent d'une manière plus " douce " la transition entre résidus de niveaux très différents. Les M-estimateurs de Huber font partie de cette classe. Ils sont associés à un mélange des normes L2 et L1, liés à un modèle de distribution gaussienne perturbée, dit gross error model. A partir de ce cadre formel, nous proposons dans cette thèse, un ensemble d'outils d'estimation et de validation de modèles paramétriques linéaires et pseudo-linéaires boîte-noires, avec extension de l'intervalle de bruit dans les petites valeurs de la constante d'accord de la norme de Huber. Nous présentons ainsi les propriétés de convergence du critère d'estimation et de l'estimateur robuste. Nous montrons que l'extension de l'intervalle de bruit réduit la sensibilité du biais de l'estimateur et améliore la robustesse aux points de levage. Pour un type de modèle pseudo-linéaire, il est présenté un nouveau contexte dit L-FTE, avec une nouvelle méthode de détermination de L, dans le but d'établir les linéarisations du gradient et du Hessien du critère d'estimation, ainsi que de la matrice de covariance asymptotique de l'estimateur. De ces relations, une version robuste du critère de validation FPE est établie et nous proposons un nouvel outil d'aide au choix de modèle estimé. Des expérimentations sur des processus simulés et réels sont présentées et analysées.L'identification des systèmes dynamiques complexes reste une préoccupation lorsque les erreurs de prédictions contiennent des outliers d'innovation. Ils ont pour effet de détériorer le modèle estimé, si le critère d'estimation est mal choisi et mal adapté. Cela a pour conséquences de contaminer la distribution de ces erreurs, laquelle présente des queues épaisses et s'écarte de la distribution normale. Pour résoudre ce problème, il existe une classe d'estimateurs, dits robustes, moins sensibles aux outliers, qui traitent d'une manière plus " douce " la transition entre résidus de niveaux très différents. Les M-estimateurs de Huber font partie de cette classe. Ils sont associés à un mélange des normes L2 et L1, liés à un modèle de distribution gaussienne perturbée, dit gross error model. A partir de ce cadre formel, nous proposons dans cette thèse, un ensemble d'outils d'estimation et de validation de modèles paramétriques linéaires et pseudo-linéaires boîte-noires, avec extension de l'intervalle de bruit dans les petites valeurs de la constante d'accord de la norme de Huber. Nous présentons ainsi les propriétés de convergence du critère d'estimation et de l'estimateur robuste. Nous montrons que l'extension de l'intervalle de bruit réduit la sensibilité du biais de l'estimateur et améliore la robustesse aux points de levage. Pour un type de modèle pseudo-linéaire, il est présenté un nouveau contexte dit L-FTE, avec une nouvelle méthode de détermination de L, dans le but d'établir les linéarisations du gradient et du Hessien du critère d'estimation, ainsi que de la matrice de covariance asymptotique de l'estimateur. De ces relations, une version robuste du critère de validation FPE est établie et nous proposons un nouvel outil d'aide au choix de modèle estimé. Des expérimentations sur des processus simulés et réels sont présentées et analysées.

Terminal localization for indoor Wireless Local Area Networks (WLAN) is critical for the deployment of location-aware computing inside of buildings. The purpose of this research work is not to develop a novel WLAN terminal location estimation technique or algorithm, but rather to tackle challenges in survey data collection and in calibration of multiple mobile terminal Received Signal Strength (RSS) data. Three major challenges are addressed in this thesis: first, to decrease the influence of outliers introduced in the distance measurements by Non-Line-of-Sight (NLoS) propagation when a ultrasonic sensor network is used for data collection; second, to obtain high localization accuracy in the presence of fluctuations of the RSS measurements caused by multipath fading; and third, to determine an automated calibration method to reduce large variations in RSS levels when different mobile devices need to be located. In this thesis, a robust window function is developed to mitigate the influence of outliers in survey terminal localization. Furthermore, spatial filtering of the RSS signals to reduce the effect of the distance-varying portion of noise is proposed. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of tight clusters and survey points uniformly distributed over the network area. Finally, an affine transformation is introduced as RSS calibration method between mobile devices to decrease the effect of RSS level variation and an automated calibration procedure based on the Expectation-Maximization (EM) algorithm is developed. The results show that the mean distance error in the survey terminal localization is well within an acceptable range for data collection. In addition, when the spatial averaging noise reduction filter is used the location accuracy improves by 16% and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. Lastly, the location accuracy is within 2m when an affine function is used for RSS calibration and the automated calibration algorithm converged to the optimal transformation parameters after it was iterated for 11 locations.

L'identification des systèmes dynamiques complexes reste une préoccupation lorsque les erreurs de prédictions contiennent des outliers d'innovation. Ils ont pour effet de détériorer le modèle estimé, si le critère d'estimation est mal choisi et mal adapté. Cela a pour conséquences de contaminer la distribution de ces erreurs, laquelle présente des queues épaisses et s'écarte de la distribution normale. Pour résoudre ce problème, il existe une classe d'estimateurs, dits robustes, moins sensibles aux outliers, qui traitent d'une manière plus « douce » la transition entre résidus de niveaux très différents. Les M-estimateurs de Huber font partie de cette classe. Ils sont associés à un mélange des normes L2 et L1, liés à un modèle de distribution gaussienne perturbée, dit gross error model. A partir de ce cadre formel, nous proposons dans cette thèse, un ensemble d'outils d'estimation et de validation de modèles paramétriques linéaires et pseudo-linéaires boîte-noires, avec extension de l'intervalle de bruit dans les petites valeurs de la constante d'accord de la norme de Huber. Nous présentons ainsi les propriétés de convergence du critère d'estimation et de l'estimateur robuste. Nous montrons que l'extension de l'intervalle de bruit réduit la sensibilité du biais de l'estimateur et améliore la robustesse aux points de levage. Pour un type de modèle pseudo-linéaire, il est présenté un nouveau contexte dit L-FTE, avec une nouvelle méthode de détermination de L, dans le but d'établir les linéarisations du gradient et du Hessien du critère d'estimation, ainsi que de la matrice de covariance asymptotique de l'estimateur. De ces relations, une version robuste du critère de validation FPE est établie et nous proposons un nouvel outil d'aide au choix de modèle estimé. Des expérimentations sur des processus simulés et réels sont présentées et analysées.L'identification des systèmes dynamiques complexes reste une préoccupation lorsque les erreurs de prédictions contiennent des outliers d'innovation. Ils ont pour effet de détériorer le modèle estimé, si le critère d'estimation est mal choisi et mal adapté. Cela a pour conséquences de contaminer la distribution de ces erreurs, laquelle présente des queues épaisses et s'écarte de la distribution normale. Pour résoudre ce problème, il existe une classe d'estimateurs, dits robustes, moins sensibles aux outliers, qui traitent d'une manière plus « douce » la transition entre résidus de niveaux très différents. Les M-estimateurs de Huber font partie de cette classe. Ils sont associés à un mélange des normes L2 et L1, liés à un modèle de distribution gaussienne perturbée, dit gross error model. A partir de ce cadre formel, nous proposons dans cette thèse, un ensemble d'outils d'estimation et de validation de modèles paramétriques linéaires et pseudo-linéaires boîte-noires, avec extension de l'intervalle de bruit dans les petites valeurs de la constante d'accord de la norme de Huber. Nous présentons ainsi les propriétés de convergence du critère d'estimation et de l'estimateur robuste. Nous montrons que l'extension de l'intervalle de bruit réduit la sensibilité du biais de l'estimateur et améliore la robustesse aux points de levage. Pour un type de modèle pseudo-linéaire, il est présenté un nouveau contexte dit L-FTE, avec une nouvelle méthode de détermination de L, dans le but d'établir les linéarisations du gradient et du Hessien du critère d'estimation, ainsi que de la matrice de covariance asymptotique de l'estimateur. De ces relations, une version robuste du critère de validation FPE est établie et nous proposons un nouvel outil d'aide au choix de modèle estimé. Des expérimentations sur des processus simulés et réels sont présentées et analysées. / Complex dynamic systems identification remains a concern when prediction errors contain innovation outliers. They have the effect to damage the estimated model if the estimation criterion is badly chosen and badly adapted. The consequence is the contamination of the distribution of these errors; this distribution presents heavy tails and deviates of the normal distribution. To solve this problem, there is a robust estimator's class, less sensitive to the outliers, which treat the transition between residuals of very different levels in a softer way. The Huber's M-estimators belong to this class. They are associated to a mixed L2 - L1 norm, related to a disturbed Gaussian distribution model, namely gross error model. From this formal context, in this thesis we propose a set of estimation and validation tools of black-box linear and pseudo-linear models, with extension of the noise interval to low values of the tuning constant in the Huber's norm. We present the convergence properties of the robust estimation criterion and the robust estimator. We show that the extension of the noise interval reduces the sensitivity of the bias of the estimator and improves the robustness to the leverage points. Moreover, for a pseudo-linear model structure, we present a new context, named L-FTE, with a new method to determine L, in order to linearize the gradient and the Hessien of estimation criterion and the asymptotic covariance matrix of the estimator. From these expressions, a robust version of the FPE validation criterion is established and we propose a new decisional tool for the estimated model choice. Experiments on simulated and real systems are presented and analyzed.

Η αντιμετώπιση της περιορισμένης χωρικής ανάλυσης των εικόνων, η οποία οφείλεται στους φυσικούς περιορισμούς που εμφανίζουν οι αισθητήρες σύλληψης εικόνας, αποτελεί το αντικείμενο μελέτης της παρούσας διδακτορικής διατριβής. Στη διατριβή αυτή αρχικά γίνεται προσπάθεια μοντελοποίησης της λειτουργίας του ψηφιοποιητή εικόνας κατά τη δημιουργία αντίγραφου ενός εγγράφου μέσω απλών μοντέλων. Στην εξομοίωση της λειτουργίας του ψηφιοποιητή, το προτεινόμενο μοντέλο θα πρέπει να προτιμηθεί έναντι των μοντέλων Gaussian και Cauchy, που συναντώνται στη βιβλιογραφία, καθώς είναι ισοδύναμο στην απόδοση, απλούστερο στην υλοποίηση και δεν παρουσιάζει εξάρτηση από συγκεκριμένα χαρακτηριστικά λειτουργίας του ψηφιοποιητή. Έπειτα, μορφοποιούνται νέες μέθοδοι για τη βελτίωση της χωρικής ανάλυσης σε εικόνες. Προτείνεται μέθοδος μη ομοιόμορφης παρεμβολής για ανακατασκευή εικόνας Super-Resolution (SR). Αποδεικνύεται πειραματικά πως η προτεινόμενη μέθοδος η οποία χρησιμοποιεί την παρεμβολή Kriging υπερτερεί της μεθόδου η οποία δημιουργεί το πλέγμα υψηλής ανάλυσης μέσω της σταθμισμένης παρεμβολής κοντινότερου γείτονα που αποτελεί συμβατική τεχνική. Επίσης, παρουσιάζονται τρεις νέες μέθοδοι για στοχαστική ανακατασκευή εικόνας SR regularized. Ο εκτιμητής Tukey σε συνδυασμό με το Bilateral Total Variation (BTV) regularization, ο εκτιμητής Lorentzian σε συνδυασμό με το BTV regularization και ο εκτιμητής Huber συνδυασμένος με το BTV regularization είναι οι τρεις μέθοδοι που προτείνονται. Μία πρόσθετη καινοτομία αποτελεί η απευθείας σύγκριση των τριών εκτιμητών Tukey, Lorentzian και Huber στην ανακατασκευή εικόνας super-resolution, άρα στην απόρριψη outliers. Η απόδοση των προτεινόμενων μεθόδων συγκρίνεται απευθείας με εκείνη μίας τεχνικής SR regularized που υπάρχει στη βιβλιογραφία, η οποία αποδεικνύεται κατώτερη. Σημειώνεται πως τα πειραματικά αποτελέσματα οδηγούν σε επαλήθευση της θεωρίας εύρωστης στατιστικής συμπεριφοράς. Επίσης, εκπονείται μία πρωτότυπη μελέτη σχετικά με την επίδραση που έχει κάθε ένας από τους όρους έκφρασης πιστότητας στα δεδομένα και regularization στη διαμόρφωση του αποτελέσματος της ανακατασκευής εικόνας SR. Τα συμπεράσματα που προκύπτουν βοηθούν στην επιλογή μίας αποτελεσματικής μεθόδου για ανακατασκευή εικόνας SR ανάμεσα σε διάφορες υποψήφιες μεθόδους για κάποια δεδομένη ακολουθία εικόνων χαμηλής ανάλυσης. Τέλος, προτείνεται μία μέθοδος παρεμβολής σε εικόνα μέσω νευρωνικού δικτύου. Χάρη στην προτεινόμενη τεχνική εκπαίδευσης το νευρωνικό δίκτυο μαθαίνει το point spread function του ψηφιοποιητή εικόνας. Τα πειραματικά αποτελέσματα αποδεικνύουν πως η προτεινόμενη μέθοδος υπερτερεί σε σχέση με τους κλασικούς αλγόριθμους δικυβικής παρεμβολής και παρεμβολής spline. Η τεχνική που προτείνεται εξετάζει για πρώτη φορά το ζήτημα της σειράς της παρουσίασης των δεδομένων εκπαίδευσης στην είσοδο του νευρωνικού δικτύου. / Coping with the limited spatial resolution of images, which is caused by the physical limitations of image sensors, is the objective of this thesis. Initially, an effort to model the scanner function when generating a document copy by means of simple models is made. In a task of scanner function simulation the proposed model should be preferred over the Gaussian and Cauchy models met in bibliography as it is equivalent in performance, simpler in implementation and does not present any dependence on certain scanner characteristics. Afterwards, new methods for improving images spatial resolution are formulated. A nonuniform interpolation method for Super-Resolution (SR) image reconstruction is proposed. Experimentation proves that the proposed method employing Kriging interpolation predominates over the method which creates the high-resolution grid by means of the weighted nearest neighbor interpolation that is a conventional interpolation technique. Also, three new methods for stochastic regularized SR image reconstruction are presented. The Tukey error norm in combination with the Bilateral Total Variation (BTV) regularization, the Lorentzian error norm in combination with the BTV regularization and the Huber error norm combined with the BTV regularization are the three proposed methods. An additional novelty is the direct comparison of the three estimators Tukey, Lorentzian and Huber in the task of super-resolution image reconstruction, thus in rejecting outliers. The performance of the proposed methods proves superior to that of a regularized SR technique met in bibliography. Experimental results verify the robust statistics theory. Moreover, a novel study which considers the effect of each one of the data-fidelity and regularization terms on the SR image reconstruction result is carried out. The conclusions reached help to select an effective SR image reconstruction method, among several potential ones, for a given low-resolution sequence of frames. Finally, an image interpolation method employing a neural network is proposed. The presented training procedure results in the network learning the scanner point spread function. Experimental results prove that the proposed technique predominates over the classical algorithms of bicubic and spline interpolation. The proposed method is novel as it treats, for the first time, the issue of the training data presentation order to the neural network input.

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