Master's thesis deals with use of electronic instrument transformers (sensors) in the protection system in medium-voltage substation. Substation consists of 2 incoming feeders, 2 outgoing feeders for motors, 2 outgoing feeders for power transformers, measuring, bus coupler and bus riser feeder. Incoming feeders are connected to distribution system E.ON by cable lines which were proposed. Protected machines (power transformers and motors with rated power) are connected to switchgear panels of UniGear ZS1 type by cable lines too. Proposed protection system is based on the short-circuit conditions, standard CSN 33 3051 recommendations as well as theoretical backgrounds acquired from technical papers and other publicated literature according to the bibliography. For selected protection functions are defined their parameters. Control, monitoring and protection functions provides REF 542plus relay. Consequently, secondary tests which are part of the commissioning, are given in the practical part of thesis. Secondary tests were performed by relay test system FREJA 300 by Megger. Results of tests are displayed in tripping characteristics.

Presented diploma thesis focuses on the study of diffusion of cupric ions in humic acid gels. A total of fifth different standards of humic acids and one sample humic acid prepared from same source as in bachelor's thesis, on which this thesis continues, were used for preparation solutions of humic acids. Thereafter, these solutions were used for preparation of agarose hydrogels, which were necessary in following diffusion experiments. The objective of the work was to compare transport properties of humic standards between themselves and then compare standards with humic acid prepared from same source as in bachelor's thesis. Measure, which was used to determine the transport properties, was comparison of effective diffusion coefficients. Method of instantaneous planar source diffusion was used to compare them. This method was based monitoring temporal evolution of diffusion profiles of cupric ions in humic hydrogels. Copper ions were selected as diffusing medium because of their high affinity and strong bonds to humic acids.

La crise financière de ces dernières années a relancé le débat sur le caractère dit « sans risque de défaut » des obligations souveraines. Face aux enjeux économiques et financiers, les établissements de crédit et les Institutions Financières ont du revoir les méthodes d’évaluation des obligations. Cette thèse a pour objectif la modélisation et la Gestion des prix obligataires et s’articule autour de quatre points. Dans le premier point, nous avons présenté les approches théoriques portant sur les modèles traditionnels des taux d’intérêt. Dans le second point, nous avons conçu un modèle test nommé M-M en discrétisant les modèles à temps continu du taux d’intérêt court et en recourant aux modèles de la famille GARCH. Ce modèle est construit en incorporant les effets niveau des taux d’intérêt à court terme et GARCH (1,1). Les résultats de l’estimation du modèle M-M suggère la nécessité de tenir compte des deux effets pour la modélisation des rendements des bons du Trésor américain. Le troisième point consiste à extraire les facteurs que l’on peut interpréter comme le niveau, la pente et la courbure. Ces facteurs sont extraits à partir de deux modèles qui sont des extensions dynamiques de la fonctionnelle de Nelson et Siegel. Les courbes des taux utilisés sont celles des Etats-Unis, de la France et de l’Afrique du Sud. La présence de l’Afrique du Sud dans cette étude est due à notre envie de traiter la structure par terme des taux d’intérêt d’un pays africain et aussi son économie émergente. A l’aide des proxies, et d’une ACP sur la courbe des taux de ces trois pays, ces facteurs ont été analysés sur la base de leur qualité d’ajustement. Le dernier point a pour but de traiter les indicateurs macroéconomiques et financiers qui peuvent expliquer les facteurs endogènes extraits. / The financial crisis of recent years has re-opened the debate of the so-called "risk-free" government bonds. Faced with economic and financial issues, credit institutions and financial institutions had reviewed the methods of bonds evaluation. The aim of this thesis is the modeling and management of the bonds prices and is organized on four points. In the first point, we present theoretical approaches on traditional models of interest rates. In the second point, we design a test model named M-M by discretizing the continuous-time models of the short interest rate and using the GARCH family models. This model is constructed by incorporating the level effect of the short term interest rates and GARCH (1,1) effect. The M-M estimation results suggest considering both effects for modeling Treasury bills yields. The third point determines the factors that can be interpreted as the level, slope and curvature, these factors are extracted from two models that are dynamics extensions of the Nelson and Siegel functional. We use Yield Curves of the United States, France and South Africa. The presence of South Africa in this study is due to our desire to treat the term structure of interest rates in an African country which is an emerging economy as well. These factors were analyzed on the basis of their goodness of fit. The last point aims to address macroeconomic and financial indicators that can explain the endogenous factors.

No description available.

Growth and development are central constituents of the human experience. Although the American Psychological Association aims to understand change and behavior in ways that embrace all aspects of experience (APA, 2008), sudden, life-altering or quantum transformation has been disregarded throughout the history of psychology until recently (see Miller & C' de Baca, 1994, 2001). Quantum transformation is similar to self-surrender conversion (James, 1902), but different from peak experiences (Maslow, 1964) and near death experiences (Lorimer, 1990) because quantum transformation, by definition, involves lasting change. Quantum transformation contains epistemic qualities, which refer to the content and process of knowing (Miller & C' de Baca, 2001), but little is known about these qualities. The current study employed a qualitative method to better understand the epistemic qualities of quantum transformation. Fourteen participants were extensively interviewed about their experience. Analysis involved hermeneutic methods (Kvale, 1996) and phenomenological description (Giorgi & Giorgi, 2003). Quantum transformation is essentially a process of knowing that unfolded in the form of Disintegration, Insight, and Integration in the present study. First, Disintegration is presented by themes of Overwhelming stress, Relational struggle, Hopelessness, Holding-on, Control, Psychological turmoil, Self-discrepancy, and Guilt. Second, Insight is presented by the Content and Tacit knowing of the experience. Third, Integration is presented by Changes in values, Other-orientation, and A process of development. The results suggest that the disintegration and the suffering that characterizes the pre-transformation milieu inform how quantum transformation relates to lasting change. Therapists that automatically aim to alleviate moral-emotional sorrow or guilt should consider whether the emotional experience can bring about positive transformation. Overall, quantum transformation has potentially major implications for our understanding of personality change and moral development.

No description available.

[EN] Microwave photonics (MWP) is a well-established research field that investigates the use of photonic technologies to generate, distribute, process and analyze RF waveforms in the optical domain. Despite its great potential to solve long-standing problems faced by both the microwave and electronics industries, MWP systems are bulky, expensive and consume a lot of power. Integrated microwave photonics (IMWP) is an emerging area of research that promises to alleviate most of these drawbacks through the use of photonic integrated circuits (PIC). In this work, we have aimed at further closing the gap between the worlds of MWP and integrated optics. In particular, we have focused on the design and experimental characterization of PICs with reconfigurable, ring-assisted Mach-Zehnder interferometer filters (RAMZI), and demonstrated its potential use in different IMWP applications. These filters consist of a symmetric MZI loaded with ring resonators, which are coupled to the MZI branches by different optical couplers. The contributions of this thesis can be split into two sections. In the first one, we demonstrate integrated optical couplers and reflectors with variable power splitting and reflections ratios. These exploit the well-known properties of tapered multimode interference couplers (MMI), and their inherent robustness makes them highly suitable for the implementation of both RAMZI and reflective filters. Besides, we study in detail the impact of manufacturing deviations in the performance of a 4x4 MMI-based 90º hybrid, which is a fundamental building block in coherent optical communication systems. In the second section, we demonstrate the use of integrated RAMZI filters for three different IMWP applications, including instantaneous frequency measurement (IFM), direct detection of frequency-modulated signals in a MWP link, as well as in tunable, coherent MWP filters. A theoretical analysis of the limits and trade-offs that exist in photonics-based IFM systems is also provided. Even though these are early proof-of-concept experiments, we hope that further technological developments in the field will finally turn MWP into a commercial reality. / [ES] La fotónica de microondas (MWP) es un campo de investigación que estudia el uso de tecnologías ópticas para generar, distribuir, procesar y analizar señales de RF. A pesar de su gran potencial para resolver algunos de los problemas a los que se enfrentan las industrias electrónica y de microondas, estos sistemas son voluminosos, caros y consumen mucha potencia. La fotónica de microondas integrada (IMWP) es un área emergente que promete solucionar todos estos inconvenientes a través de la utilización de circuitos ópticos integrados (PIC). En esta tesis, hemos pretendido avanzar un poco más en el acercamiento entre estas dos disciplinas. En concreto, nos hemos centrado en el diseño y caracterización experimental de PICs con filtros reconfigurables basados en interferómetros Mach-Zehnder cargados con anillos (RAMZI), y demostrado su potencial uso en diferentes aplicaciones de IMWP. Los filtros RAMZI están hecho básicamente de un MZI simétrico cargado con anillos, los cuales a su vez se acoplan a las ramas del interferómetro a través de distintos acopladores ópticos. Las contribuciones de este trabajo se pueden dividir en dos partes. En la primera, hemos demostrado acopladores y reflectores ópticos integrados con coeficientes de acoplo y reflexión variables. Éstos explotan las propiedades de los acopladores por interferencia multimodal (MMI), y su robustez les hace muy atractivos para la implementación de filtros RAMZI y de tipo reflectivo. Además, hemos analizado el impacto que las tolerancias de fabricación tienen en el rendimiento de un híbrido óptico de 90º basado en un MMI 4x4, el cual es un elemento fundamental en los sistemas de comunicaciones ópticas coherentes. En la segunda parte, hemos demostrado el uso de filtros RAMZI en tres aplicaciones distintas de IMWP. En concreto, hemos utilizado dichos filtros para implementar sistemas de medida de frecuencia instantánea (IFM), detección directa de señales moduladas en frecuencia para enlaces fotónicos, así como en filtros coherentes y sintonizables de MWP. También hemos desarrollado un análisis teórico de las limitaciones y problemas que existen en los sistemas IFM. A pesar de que todos los experimentos realizados han consistido en prototipos para una prueba de concepto, esperamos que futuros avances tecnológicos permitan que la fotónica de microondas se convierta algún día en una realidad comercial. / [CA] La fotònica de microones (MWP) és un camp d'investigació que estudia l'ús de tecnologies òptiques per a generar, distribuir, processar y analitzar senyals de radiofreqüència. A pesar del seu gran potencial per a resoldre alguns dels problemes als que s'enfronten les indústries electrònica i de microones, estos sistemes son voluminosos, cars i consumixen molta potència. La fotònica de microones integrada (IMWP) és un àrea emergent que promet solucionar tots estos inconvenients a través de la utilització de circuits òptics integrats (PIC). En esta tesi, hem pretés avançar un poc més en l'acostament entre estes dos disciplines. En concret, ens hem centrat en el disseny i caracterització experimental de PICs amb filtres reconfigurables basats en interferòmetres Mach-Zehnder carregats amb anells (RAMZI), i demostrat el seu potencial en diferents aplicacions d' IMWP. Els filtres RAMZI estan fets bàsicament d'un MZI simètric carregat amb anells, els quals, al seu torn, s'acoblen a les branques del interferòmetre a través de distints acobladors òptics. Les contribucions d'este treball es poden dividir en dos parts. En la primera, hem demostrat acobladors i reflectors òptics integrats amb coeficients de transmissió i reflexió variables. Estos exploten les propietats dels acobladors per interferència multimodal (MMI), i la seua robustesa els fa molt atractius per a la implementació de filtres RAMZI i de tipo reflectiu. A més a més, hem analitzat l'impacte que les toleràncies de fabricació tenen en el rendiment d'un híbrid òptic de 90 graus basat en un MMI 4x4, el qual és un element fonamental en els sistemes de comunicacions òptiques coherents. En la segona part, hem demostrat l'ús de filtres RAMZI en tres aplicacions diferents de IMWP. En concret, hem utilitzat estos filtres per a implementar sistemes de mesura de freqüència instantània (IFM), detecció directa de senyals modulades en freqüència per a enllaços fotònics, així com en filtres coherents i sintonitzables de MWP. També hem desenvolupat una anàlisi teòrica de les limitacions i problemes que existixen en els sistemes IFM. A pesar de que tots els experiments realitzats han consistit en prototips per a una prova de concepte, esperem que futurs avanços tecnològics permeten que la fotònica de microones es convertisca algun dia en una realitat comercial. / Sánchez Fandiño, JA. (2016). Integrated Optical Filters for Microwave Photonic Applications [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/67690

Travel-time information is essential in Advanced Traveler Information Systems (ATISs) and Advanced Traffic Management Systems (ATMSs). A key component of these systems is the prediction of the spatiotemporal evolution of roadway traffic state and travel time. From the perspective of travelers, such information can result in better traveler route choice and departure time decisions. From the transportation agency perspective, such data provide enhanced information with which to better manage and control the transportation system to reduce congestion, enhance safety, and reduce the carbon footprint of the transportation system. The objective of the research presented in this dissertation is to develop a framework that includes three major categories of methodologies to predict the spatiotemporal evolution of the traffic state. The proposed methodologies include macroscopic traffic modeling, computer vision and recursive probabilistic algorithms. Each developed method attempts to predict traffic state, including roadway travel times, for different prediction horizons. In total, the developed multi-tool framework produces traffic state prediction algorithms ranging from short – (0~5 minutes) to medium-term (1~4 hours) considering departure times up to an hour into the future. The dissertation first develops a particle filter approach for use in short-term traffic state prediction. The flow continuity equation is combined with the Van Aerde fundamental diagram to derive a time series model that can accurately describe the spatiotemporal evolution of traffic state. The developed model is applied within a particle filter approach to provide multi-step traffic state prediction. The testing of the algorithm on a simulated section of I-66 demonstrates that the proposed algorithm can accurately predict the propagation of shockwaves up to five minutes into the future. The developed algorithm is further improved by incorporating on- and off-ramp effects and more realistic boundary conditions. Furthermore, the case study demonstrates that the improved algorithm produces a 50 percent reduction in the prediction error compared to the classic LWR density formulation. Considering the fact that the prediction accuracy deteriorates significantly for longer prediction horizons, historical data are integrated and considered in the measurement update in the developed particle filter approach to extend the prediction horizon up to half an hour into the future. The dissertation then develops a travel time prediction framework using pattern recognition techniques to match historical data with real-time traffic conditions. The Euclidean distance is initially used as the measure of similarity between current and historical traffic patterns. This method is further improved using a dynamic template matching technique developed as part of this research effort. Unlike previous approaches, which use fixed template sizes, the proposed method uses a dynamic template size that is updated each time interval based on the spatiotemporal shape of the congestion upstream of a bottleneck. In addition, the computational cost is reduced using a Fast Fourier Transform instead of a Euclidean distance measure. Subsequently, the historical candidates that are similar to the current conditions are used to predict the experienced travel times. Test results demonstrate that the proposed dynamic template matching method produces significantly better and more stable prediction results for prediction horizons up to 30 minutes into the future for a two hour trip (prediction horizon of two and a half hours) compared to other state-of-the-practice and state-of-the-art methods. Finally, the dissertation develops recursive probabilistic approaches including particle filtering and agent-based modeling methods to predict travel times further into the future. Given the challenges in defining the particle filter time update process, the proposed particle filtering algorithm selects particles from a historical dataset and propagates particles using data trends of past experiences as opposed to using a state-transition model. A partial resampling strategy is then developed to address the degeneracy problem in the particle filtering process. INRIX probe data along I-64 and I-264 from Richmond to Virginia Beach are used to test the proposed algorithm. The results demonstrate that the particle filtering approach produces less than a 10 percent prediction error for trip departures up to one hour into the future for a two hour trip. Furthermore, the dissertation develops an agent-based modeling approach to predict travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in the decision making system, which predicts the travel time for each time interval according to past experiences from a historical dataset. A set of agent interactions are developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents with negligible weights with new agents. Consequently, the aggregation of each agent's recommendation (predicted travel time with associated weight) provides a macroscopic level of output – predicted travel time distribution. The case study demonstrated that the agent-based model produces less than a 9 percent prediction error for prediction horizons up to one hour into the future. / Ph. D.

Signal processing has been playing a key role in providing solutions to key problems encountered in communications, in general, and in wireless communications, in particular. Time-Frequency Signal Processing (TFSP) provides eective tools for analyzing nonstationary signals where the frequency content of signals varies in time as well as for analyzing linear time-varying systems. This research aimed at exploiting the advantages of TFSP, in dealing with nonstationary signals, into the fundamental issues of signal processing, namely the signal estimation and signal separation. In particular, it has investigated the problems of (i) the Instantaneous Frequency (IF) estimation of Linear Frequency-Modulated (LFM) signals corrupted in complex-valued zero-mean Multiplicative Noise (MN), and (ii) the Underdetermined Blind Source Separation (UBSS) of LFM signals, while focusing onto the fast-growing area of Wireless Communications (WCom). A common problem in the issue of signal estimation is the estimation of the frequency of Frequency-Modulated signals which are seen in many engineering and real-life applications. Accurate frequency estimation leads to accurate recovery of the true information. In some applications, the random amplitude modulation shows up when the medium is dispersive and/or when the assumption of point target is not valid; the original signal is considered to be corrupted by an MN process thus seriously aecting the recovery of the information-bearing frequency. The IF estimation of nonstationary signals corrupted by complex-valued zero-mean MN was investigated in this research. We have proposed a Second-Order Statistics approach, rather than a Higher-Order Statistics approach, for IF estimation using Time-Frequency Distributions (TFDs). The main assumption was that the autocorrelation function of the MN is real-valued but not necessarily positive (i.e. the spectrum of the MN is symmetric but does not necessary has the highest peak at zero frequency). The estimation performance was analyzed in terms of bias and variance, and compared between four dierent TFDs: Wigner-Ville Distribution, Spectrogram, Choi-Williams Distribution and Modified B Distribution. To further improve the estimation, we proposed to use the Multiple Signal Classification algorithm and showed its better performance. It was shown that the Modified B Distribution performance was the best for Signal-to-Noise Ratio less than 10dB. In the issue of signal separation, a new research direction called Blind Source Separation (BSS) has emerged over the last decade. BSS is a fundamental technique in array signal processing aiming at recovering unobserved signals or sources from observed mixtures exploiting only the assumption of mutual independence between the signals. The term "blind" indicates that neither the structure of the mixtures nor the source signals are known to the receivers. Applications of BSS are seen in, for example, radar and sonar, communications, speech processing, biomedical signal processing. In the case of nonstationary signals, a TF structure forcing approach was introduced by Belouchrani and Amin by defining the Spatial Time- Frequency Distribution (STFD), which combines both TF diversity and spatial diversity. The benefit of STFD in an environment of nonstationary signals is the direct exploitation of the information brought by the nonstationarity of the signals. A drawback of most BSS algorithms is that they fail to separate sources in situations where there are more sources than sensors, referred to as UBSS. The UBSS of nonstationary signals was investigated in this research. We have presented a new approach for blind separation of nonstationary sources using their TFDs. The separation algorithm is based on a vector clustering procedure that estimates the source TFDs by grouping together the TF points corresponding to "closely spaced" spatial directions. Simulations illustrate the performances of the proposed method for the underdetermined blind separation of FM signals. The method developed in this research represents a new research direction for solving the UBSS problem. The successful results obtained in the research development of the above two problems has led to a conclusion that TFSP is useful for WCom. Future research directions were also proposed.

[ES] Esta tesis de doctorado está dedicada al problema de descomposición de señales no estacionarias en componentes modales, entendida como componentes oscilatorias independientes, con amplitud y fase dependientes del tiempo. Para este fin, se propone un enfoque metodológico basado en representaciones en espacio de estados diagonales en bloques. Una contribución teórica primaria de esta tesis consiste en demostrar que la respuesta de un sistema de espacio de estados diagonal en bloques puede ser representada en una forma modal con amplitudes y frecuencias dependientes del tiempo. Subsecuentemente, construyendo sobre este resultado, un marco de trabajo basado en filtros de Kalman se propone para la descomposición modal de señales no estacionarias. Como resultado, una familia de métodos paramétricos para la descomposición modal de señales no estacionarias univariadas y multivariadas basadas en representaciones de espacio de estados diagonales en bloques y filtros de Kalman ha sido postulada. La representación básica está construida en bloques de segundo orden, cada uno de los cuales representa los componentes en fase y en cuadratura de un único componente oscilatorio no estacionario. Así, la respuesta total es construida como la suma ponderada de cada uno de estos modos. La identificación de estos modelos requiere la estimación conjunta de las trayectorias y los parámetros modales dependientes del tiempo, así como los hiperparámetros del modelo, constituidos por la matriz de mezcla de modos, las matrices de covarianza del vector de estados, de parámetros y del ruido de medición, y las condiciones iniciales. Para este propósito, un algoritmo de Expectación-Maximización ha sido adaptado como parte de esta tesis. La metodología obtenida es entonces evaluada en la descomposición y eliminación de ruido de registros electrocardiográficos (ECG), los cuales consisten en componentes no-estacionarias pseudo-periódicas y son susceptibles a diferentes tipos de interferencias. La estructura de estas señales las hace susceptibles a las descomposiciones modales basadas propuestas en esta tesis. A diferencia de otros métodos populares de descomposición de señales, las descomposiciones obtenidas con la metodología propuesta proveen componentes oscilatorios con interpretabilidad física y que proveen resultados consistentes para señales multivariadas, como en el caso de registros de ECG con múltiples derivaciones. Otra estrategia que se desarrolló en este proyecto investigativo lo constituye la aplicación de la transformada delta u operador de Euler al filtro de Kalman, esto condujo a resultados de alta precisión en la extracción de componentes de banda angosta. La metodología propuesta constituye una herramienta confiable para la descomposición modal en línea de señales no estacionarias multicomponentes, con resultados excelentes / [CA] Esta tesi de doctorat està dedicada al problema de descomposició de senyals no-estacionaris en components modals, entesa com a components oscil·latòries independents amb amplitud i fase dependents del temps. Per a este fi, es proposa un enfocament metodològic basat en representacions en espai d'estats diagonals en blocs. Una contribució teòrica primària d'esta tesi consistix a demostrar que la resposta d'un sistema d'espai d'estats diagonal en blocs pot ser representada en una forma modal amb amplituds i freqüències dependents del temps. Subseqüentment, construint sobre este resultat, un marc de treball basat en filtres de Kalman es proposa per a la descomposició modal de senyals no estacionaris. Com a resultat, una família de mètodes paramètrics per a la descomposició modal de senyals no estacionaris univariadas i multivariades basades en representacions d'espai d'estats diagonals en blocs i filtres de Kalman ha sigut postulada. La representació bàsica està construïda en blocs de segon ordre, cadascun dels quals representa els components en fase i en quadratura d'un únic component oscil·latori no estacionari. Així, la resposta total és construïda com la suma ponderada de cadascun d'estos modes. La identificació d'estos models requerix l'estimació conjunta de les trajectòries i els paràmetres modals dependents del temps, així com els hiperparámetros del model, constituïts per la matriu de mescla de modes, les matrius de covariància del vector d'estats, de paràmetres i del soroll de mesurament, i les condicions inicials. Per a este propòsit, un algorisme d'Expectació-Maximització ha sigut adaptat com a part d'esta tesi. La metodologia obtinguda és llavors avaluada en la descomposició i eliminació de soroll de registres electrocardiogràfics (ECG), els quals consistixen en components no-estacionàries pseudo-periòdiques i són susceptibles a diferents tipus d'interferències. L'estructura d'estos senyals les fa susceptibles a les descomposicions modals basades propostes en esta tesi. A diferència d'altres mètodes populars de descomposició de senyals, les descomposicions obtingudes amb la metodologia proposada proveïxen components oscil·latoris amb interpretabilidad física i que proveïxen resultats consistents per a senyals multivariats, com en el cas de registres d'ECG amb múltiples derivacions. Una altra estratègia que es va desenvolupar en este projecte investigativo el constituïx l'aplicació de la transformada delta o operador d'Euler al filtre de Kalman, això va conduir a resultats d'alta precisió en l'extracció de components de banda estreta. La metodologia proposada constituïx una eina de confiança per a la descomposició modal en línia de senyals no estacionaris multicomponents, amb resultats excel·lents. / [EN] This PhD thesis is devoted to the problem of the decomposition of non-stationary signals in modal components, understood as independent oscillatory components with time-dependent amplitude and frequency. To this end, a methodological approach based on diagonal time-dependent state space models is postulated. A primary theoretical contribution of this work is to demonstrate that the response of a system in diagonal time-dependent state space form can be cast in a modal form characterized by time-dependent amplitudes and frequencies. Subsequently, building up on this result, a Kalman filter based framework for non-stationary modal decomposition is proposed. As a result, a family of parametric modal decomposition methods is postulated for univariate and multivariate non-stationary signals based on block-diagonal time-dependent state space representations and Kalman filtering/smoothing. The representation is built upon second order blocks, each representing the in-phase and quadrature components of a single non-stationary oscillatory component. The total response is then constructed as the weighted sum of each of these modes. Accordingly, the model identification involves the joint estimation of the modal trajectories and the time-dependent modal parameters, along with the model hyperparameters, constituted by the mode mixing matrix, the state, parameter and noise covariances, and initial conditions. A tailored Expectation-Maximization algorithm is designed for this purpose as part of this thesis. The obtained methodology is assessed in the decomposition and denoising of electrocardiographic (ECG) signals, which consist of pseudo-periodic non-stationary signals and are susceptible to significant interference. The ECG signal structure makes them amenable to the proposed non-stationary modal decompositions. In contrast to other popular non-stationary signal decomposition methods, the proposed method provides a physically meaningful decomposition of oscillatory components, with consistent results for multivariate signals, such as multi-lead ECG records. Another strategy that was developed in this research project is the application of the delta transform or Euler operator to the Kalman filter, which led to highly precise results in extracting narrowband components. The proposed methodology constitutes a reliable tool for on-line modal decomposition of multi-component non-stationary signals, with results comparable and even better than other state-of-the-art methods. / Avendaño, LE. (2024). Método de descomposición modal no estacionaria basado en representación de espacio de estados con aplicación al análisis de señales ECG [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/211185