Diese Arbeit beschäftigt sich mit verschiedenen Aspekten und Anwendungen von Recurrence Plots. Nach einer Übersicht über Methoden, die auf Recurrence Plots basieren, werden neue Komplexitätsmaße eingeführt, die geometrische Strukturen in den Recurrence Plots beschreiben. Diese neuen Maße erlauben die Identifikation von Chaos-Chaos-Übergängen in dynamischen Prozessen. In einem weiteren Schritt werden Cross Recurrence Plots eingeführt, mit denen zwei verschiedene Prozesse untersucht werden. Diese bivariate Analyse ermöglicht die Bewertung von Unterschieden zwischen zwei Prozessen oder das Anpassen der Zeitskalen von zwei Zeitreihen. Diese Technik kann auch genutzt werden, um ähnliche Abschnitte in zwei verschiedenen Datenreihen zu finden. Im Anschluß werden diese neuen Entwicklungen auf Daten verschiedener Art angewendet. Methoden, die auf Recurrence Plots basieren, können an die speziellen Probleme angepaßt werden, so daß viele weitere Anwendungen möglich sind.<br /> <br /> Durch die Anwendung der neu eingeführten Komplexitätsmaße können Chaos-Chaos-Übergänge in Herzschlagdaten vor dem Auftreten einer lebensbedrohlichen Herzrhythmusstörung festgestellt werden, was für die Entwicklung neuer Therapien dieser Herzrhythmusstörungen von Bedeutung sein könnte. In einem weiteren Beispiel, in dem EEG-Daten aus einem kognitiv orientierten Experiment untersucht werden, ermöglichen diese Komplexitätsmaße das Erkennen von spezifischen Reaktionen im Gehirn bereits in Einzeltests. Normalerweise können diese Reaktionen erst durch die Auswertung von vielen Einzeltests erkannt werden.<br /> <br /> Mit der Hilfe von Cross Recurrence Plots wird die Existenz einer klimatischen Zirkulation, die der heutigen El Niño/ Southern Oscillation sehr ähnlich ist, im Nordwesten Argentiniens vor etwa 34000 Jahren nachgewiesen. Außerdem können mit Cross Recurrence Plots die Zeitskalen verschiedener Bohrlochdaten aufeinander abgeglichen werden. Diese Methode kann auch dazu genutzt werden, ein geologisches Profil mit Hilfe eines Referenzprofiles mit bekannter Zeitskala zu datieren. Weitere Beispiele aus den Gebieten der Molekularbiologie und der Spracherkennung unterstreichen das Potential dieser Methode. / In this work, different aspects and applications of the recurrence plot analysis are presented. First, a comprehensive overview of recurrence plots and their quantification possibilities is given. New measures of complexity are defined by using geometrical structures of recurrence plots. These measures are capable to find chaos-chaos transitions in processes. Furthermore, a bivariate extension to cross recurrence plots is studied. Cross recurrence plots exhibit characteristic structures which can be used for the study of differences between two processes or for the alignment and search for matching sequences of two data series. The selected applications of the introduced techniques to various kind of data demonstrate their ability. Analysis of recurrence plots can be adopted to the specific problem and thus opens a wide field of potential applications. <br /> <br /> Regarding the quantification of recurrence plots, chaos-chaos transitions can be found in heart rate variability data before the onset of life threatening cardiac arrhythmias. This may be of importance for the therapy of such cardiac arrhythmias. The quantification of recurrence plots allows to study transitions in brain during cognitive experiments on the base of single trials. Traditionally, for the finding of these transitions the averaging of a collection of single trials is needed. <br /> <br /> Using cross recurrence plots, the existence of an El Niño/Southern Oscillation-like oscillation is traced in northwestern Argentina 34,000 yrs. ago. In further applications to geological data, cross recurrence plots are used for time scale alignment of different borehole data and for dating a geological profile with a reference data set. Additional examples from molecular biology and speech recognition emphasize the suitability of cross recurrence plots.

In the present study, the author builds upon the single degree of freedom ice-structure interaction model initially proposed by Matlock, et al. (1969, 1971). The model created by Matlock, et al. (1969, 1971), assumed that the primary response of the structure would be in its fundamental mode of vibration. In order to glean a greater physical understanding of ice-structure interaction phenomena, it was critical that this study set out to develop a multi-mode forced response for the pier when a moving ice floe makes contact at a specific vertical pier location. Modal analysis is used in which the response of each mode is superposed to find the full modal response of the entire length of a pier subject to incremental ice loading. This incremental ice loading includes ice fracture points as well as loss of contact between ice and structure. In this model, the physical system is a bottom supported pier modeled as a cantilever beam. The frequencies at which vibration naturally occurs, and the mode shapes which the vibrating pier assumes, are properties which can be determined analytically and thus a more precise picture of pier vibration under ice loading is presented. Realistic conditions such as ice accumulation on the pier modeled as a point mass and uncertainties in the ice characteristics are introduced in order to provide a stochastic response. The impact of number of modes in modeling is studied as well as dynamics due to fluctuations of ice impact height as a result of typical tidal fluctuations. A Poincaré based analysis following on the research of Karr, et al. (1992) is employed to identify any periodic behavior of the system response. Recurrence plotting is also utilized to further define any existing structure of the ice-structure interaction time series for low and high speed floes. The intention of this work is to provide a foundation for future research coupling multiple piers and connecting structure for a comprehensive ice-wind-structural dynamics model. / Master of Science

In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments. / In dieser Arbeit stelle ich neue Resultate vor, welche zeigen, wie man Rekurrenzeigenschaften quasiperiodischer, dynamischer Systeme für eine Datenanalyse ausnutzen kann. Die vorgestellten Algorithmen basieren auf einer zweidimensionalen Darstellungsmethode, den Rekurrenz-Darstellungen. Quasiperiodizität ist die einfachste Dynamik, die nicht-triviale Rekurrenzen zeigt und tritt häufig in nichtlinearen Systemen auf. Nicht-triviale Rekurrenzen wurden im Zusammenhang mit dem eingeschränkten Dreikörper-problem eingeführt. In dieser Arbeit, habe ich mehrere Systeme mit quasiperiodischem Verhalten analytisch untersucht. Die erhaltenen Ergebnisse helfen die Wiederkehreigenschaften dieser Systeme im Detail zu verstehen. Basierend auf den analytischen Resultaten, schlage ich einen neuen Algorithmus vor, mit dessen Hilfe selbst in kurzen Zeitreihen zwischen chaotischem und quasiperiodischem Verhalten unterschieden werden kann. Die vorgeschlagene Methode ist besonders effizient zur Unterscheidung regulärer und chaotischer Trajektorien mischender dynamischer Systeme.Die praktische Anwendbarkeit der vorgeschlagenen Analyseverfahren auf Messdaten, habe ich gezeigt, indem ich erfolgreich Zeitreihen aus fluid-dynamischen Experimenten untersucht habe.

abstract: By extracting communication sequences from audio data collected during two separate five-person mission-planning tasks, interaction patterns in team communication were analyzed using a recurrence-based, nonlinear dynamics approach. These methods, previously successful in detecting pattern change in a three-person team task, were evaluated for their applicability to larger team settings, and their ability to detect pattern change when team members switched roles or locations partway through the study (Study 1) or change in patterns over time (Study 2). Both traditional interaction variables (Talking Time, Co-Talking Time, and Sequence Length of Interactions) and dynamic interaction variables (Recurrence Rate, Determinism, and Pattern Information) were explored as indicators and predictors of changes in team structure and performance. Results from these analyses provided support that both traditional and dynamic interaction variables reflect some changes in team structure and performance. However, changes in communication patterns were not detected. Because simultaneous conversations are possible in larger teams, but not detectable through our communication sequence methods, team pattern changes may not be visible in communication sequences for larger teams. This suggests that these methods may not be applicable for larger teams, or in situations where simultaneous conversations may occur. Further research is needed to continue to explore the applicability of recurrence-based nonlinear dynamics in the analysis of team communication. / Dissertation/Thesis / M.S. Applied Psychology 2012

Même s'ils n'appartiennent pas a une classe de signaux bien définie, les signaux transitoires se retrouvent dans plusieurs domaines pratiques très différents (comme les signaux médicaux et les signaux utilisés dans des systèmes de télécommunications), donc le développement des outils robustes et efficients pour faire leur analyse est un objectif important dans le traitement du signal. En particulier, cette thèse s'est concentrée surtout sur la résolution de quelques problèmes de traitement du signal posés par l'investigation ultrasonore de l'eau dans des conduites. Cependant, ce contexte applicatif a été utilisé seulement comme une base pour développer des outils génériques qui peuvent trouver leur utilité dans plusieurs d'autres applications. La thèse a abordé la question du traitement des signaux (transitoires) du point de vue du concept de récurrence dans l'espace des phases, qui est emprunté de la théorie des systèmes dynamiques. Nous avons montré que l'analyse du diagramme des recurrences (RPA) apporte dans le traitement du signal deux concepts importants : l'échantillon vectoriel, et la récurrence. L'utilisation de ces concepts nous a permis de généraliser et d'étendre des outils de traitement du signal bien connus, et aussi de construire des représentations de signal qui se sont révélées utiles dans des différentes tâches liées à la détection et à la caractérisation des transitoires. Essentiellement, dans cette thèse nous avons montré que la RPA peut être vue comme un cadre générique qui unifie dans une formulation commune des diverses outils bien connus dans le traitement du signal. En plus, elle généralise ces outils (à l'aide du concept des échantillons vectoriels) et les étend (en utilisant le concept de récurrence). / Although they do not belong to a very well defined class of signals, transient signals are found in many practical fields (from biological signals to signals used in telecommunication systems), so the development of robust and efficient tools for their analysis is an important objective in signal processing. In particular, this thesis was focused mainly on solving some signal analysis problems raised by the ultrasonic investigation of water in pipes. However, this applicative context was used only as a basis for developing generic tools that can find their usefulness in various other applications. The thesis addressed the issue of (transient) signal analysis from the perspective of the phase space recurrence concept, borrowed from dynamical systems theory. We showed that recurrence plot analysis (RPA) brings into the field of signal processing two important concepts: vector samples, and recurrence. The use of these concepts allowed us to generalize and extend well-known signal processing tools, as well as to build signal representations that proved to be useful in various tasks related to transient signal detection and characterization. Basically, in this thesis we have shown that RPA can be seen as a generic framework that unifies in a common formulation various well-known classic signal processing tools, which it generalizes (by using the concept of vector samples) and extends (by using the concept of recurrence).

This research focuses on addressing two pertinent problems in machine learning (ML) which are (a) the supervised classification of time series and (b) the need for large amounts of labeled images for training supervised classifiers. The novel contributions are two-fold. The first problem of time series classification is addressed by proposing to transform time series into domain-specific 2D features such as scalograms and recurrence plot (RP) images. The second problem which is the need for large amounts of labeled image data, is tackled by proposing a new way of using a reinforcement learning (RL) technique as a supervised classifier by using multimodal (joint representation) scalograms and RP images. The motivation for using such domain-specific features is that they provide additional information to the ML models by capturing domain-specific features (patterns) and also help in taking advantage of state-of-the-art image classifiers for learning the patterns from these textured images. Thus, this research proposes a multimodal fusion (MMF) - deep reinforcement learning (DRL) approach as an alternative technique to traditional supervised image classifiers for the classification of time series. The proposed MMF-DRL approach produces improved accuracy over state-of-the-art supervised learning models while needing fewer training data. Results show the merit of using multiple modalities and RL in achieving improved performance than training on a single modality. Moreover, the proposed approach yields the highest accuracy of 90.20% and 89.63% respectively for two physiological time series datasets with fewer training data in contrast to the state-of-the-art supervised learning model ChronoNet which gave 87.62% and 88.02% accuracy respectively for the two datasets with more training data.

Made available in DSpace on 2016-01-26T12:51:30Z (GMT). No. of bitstreams: 1 margaretearticobaptista_tese.pdf: 3014770 bytes, checksum: a4b4de19204259991aae1ec3ae61a0aa (MD5) Previous issue date: 2011-10-07 / In the last 30 years, the increasing health care expenditures resulted in an outburst of studies aimed at new proposals on the methodological evaluation of health services. With the aid of computing, several studies have been developed with the purpose of analyzing nonlinear and complex systems. The most outstanding among those methods was the Recurrence Plot, first described by Erickman et al. (1987).Objectives: To analyze the temporal behavior of the weekly amount of admissions by some nosologic groups (Appendix Diseases, Bacterial Diseases, Neoplastic Disease, and Acute Coronary Syndrome), which has occurred over a decade, through Recurrence Plots and Poincaré Recurrence Plots, as well as checking whether the systems are presenting a periodic, chaotic, or random behavior pattern. Material and Methods: The database containing all hospitalizations recorded at the Hospital de Base Regional Medical School Foundation (FUNFARME) of Sao Jose do Rio Preto, a teaching hospital, from January 1, 1998 to December 31, 2007 was peered into a microscope. As a reference to classify all these admissions, the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) was used. The Microsoft Office Excel 2003® was the software used to arrange the data into columns. The admissions were systematically set to the right array, such as day, month, and year. They were arranged into columns according to the uniform criteria of identification of the epidemiological weeks. The recurrence graphs and the respective quantitative analyses of recurrence were developed with the aid of the Visual Recurrence Analysis (VRA) software, which is freely available on the Internet. To perform the comparison among the behavior patterns, mathematical models of time series for random behavior pattern, series time for chaotic behavior pattern, series times for periodic behavior pattern, and series time for linear behavior pattern were constructed. And it has also been performed a comparison between the Recurrence Plots and the Quantitative Analysis of Recurrence with clinical cases of specific groups (young, adult, child, premature newborn, and brain death).Results: It has become clear that the number of weekly admissions for diseases of the appendix has had a tendency over the years from a random behavior pattern. In hospitalizations due to bacterial diseases, there was a chaotic behavior pattern and the neoplastic diseases showed a chaotic behavior pattern tending to a linear behavior pattern. Hospitalizations because of Acute Coronary Syndrome presented a predominantly linear behavior pattern. Conclusions: The visual aspects of Recurrence Plot and Poincaré Recurrence plot exhibited different patterns when comparing quantities of admissions of certain nosologic groups over a decade. The quantitative analysis of recurrence that was useful in classifying the behavior pattern of the quantities of admissions is likely to constitute a useful tool of evaluation and decision making regarding hospital administration. / Nos últimos trinta anos, o crescimento dos gastos com a atenção médica resultou numa expansão dos estudos voltados para novas propostas metodológicas sobre avaliação dos serviços de saúde. Com a utilização da informática, vários estudos têm sido desenvolvidos para análise de sistemas complexos e não lineares, destacando-se, entre esses métodos, os gráficos de recorrência, descritos pela primeira vez por Erickman et al. (1987). Objetivos: Analisar o comportamento temporal da quantidade semanal de internações por alguns grupos nosológicos (Doenças do Apêndice, Doenças Bacterianas, Doenças Neoplásicas e por Síndrome Coronária Aguda) ocorridas ao longo de uma década, por meio de Gráficos de Recorrência e Gráficos de Poincaré e verificar se são sistemas que apresentam comportamentos periódicos, aleatórios ou caóticos. Material e Método: Foi avaliado o banco de dados contendo todas as internações no Hospital de Base da Fundação Faculdade Regional de Medicina de São José do Rio Preto, no período de 01 de janeiro de 1998 a 31 de dezembro de 2007. Como referência para classificação dessas internações, utilizou-se a Décima Revisão da Classificação Internacional de Doenças e de Problemas Relacionados à Saúde (CID 10). Foi utilizado o programa Microsoft Office Excel 2003 para a tabulação dos dados. As internações foram ordenadas em dia, mês, ano e tabuladas, seguindo o critério uniforme de identificação das semanas epidemiológicas. Os gráficos de recorrência e respectiva análise quantitativa foram construídos com o auxílio do software Visual Recurrence Analysis (VRA), disponível gratuitamente na Internet. Para realizar a comparação de padrões de comportamentos foram construídos modelos matemáticos de séries temporais aleatória, caótica, periódica e linear. E também foi realizada comparação entre Gráficos de Recorrência e Análise Quantitativa da Recorrência com casos clínicos de grupos específicos (jovem adulto, criança, Recém- nascido prematuro e morte cerebral). Resultados: Evidenciou-se que a quantidade de internações semanal por doenças do apêndice tiveram uma tendência ao longo dos anos de comportamento aleatório. Nas internações por doenças bacterianas houve comportamento caótico e as internações por doenças neoplásicas apresentaram um comportamento caótico tendendo a linear. As internações por Síndrome Coronária Aguda apresentaram predominantemente comportamento linear, Conclusões: Os aspectos visuais dos Gráficos de Recorrência e de Poincaré exibiram padrões diferentes na comparação entre quantidades de internações de determinados grupos nosológicos ao longo de uma década. A análise quantitativa da recorrência que auxiliou na classificação do comportamento das quantidades de internações e pode constituir-se em ferramenta útil de avaliação e tomada de decisão em administração hospitalar.

Submitted by Eunice Novais (enovais@uepg.br) on 2018-04-18T18:15:46Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Santos, Moises Souza.pdf: 3654988 bytes, checksum: 6bcf0d0867a3d40291ae626664114a49 (MD5) / Made available in DSpace on 2018-04-18T18:15:46Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Santos, Moises Souza.pdf: 3654988 bytes, checksum: 6bcf0d0867a3d40291ae626664114a49 (MD5) Previous issue date: 2018-03-01 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / A importância do estudo de estados quimera em redes neuronais reflete no fato destes possuírem uma forte ligação com alguns tipos de anomalias diagnosticadas no cérebro, por exemplo, epilepsia,mal de Parkinson e Alzheimer. Neste trabalho, realizamos um estudo da aplicação dos gráficos de recorrência, em sua versão espacial, na caracterização da coexistência de estados coerentes e incoerentes em sistemas dinâmicos acoplados. Utilizamos um modelo constituído de osciladores de fase para uma primeira abordagem da matriz de recorrência. Nossos resultados indicam que os diagnósticos quantitativos, baseados no gráfico de recorrência, detectam não só a existência de estados quimera como também estados sincronizados e dessincronizados que por ventura emergem na rede. Sobre esse aspecto, mostramos que a análise via recorrência espacial é superior à utilização do parâmetro de ordem global pós-colapso de estados quimera. Este cenário ocorre em algumas situações onde a rede exibe quimera e esta subitamente desaparece do sistema, que passa a exibir um comportamento sincronizado na frequência de seus osciladores. Neste caso, o parâmetro de ordem global não identifica esta mudança de comportamento sendo necessário uma interpretação via outro diagnóstico. Também utilizamos a rede de conectividade cortical de gato, como forma de acoplamento, e distinguimos duas formas de estados híbridos: uma quimera com a região incoerente em dinâmica temporal de spikes e outra quimera onde a região incoerente apresenta dinâmica temporal de bursts. Identificamos que este último caso de estados quimera possui maior robustez com relação à perturbação externa aplicada no sistema.Concluímos que a região de quimera com bursts necessita de uma intensidade de perturbação duas vezes superior que a região de spikes para deixar de existir na rede de neurônios. / A importância do estudo de estados quimera em redes neuronais reflete no fato destes possuírem uma forte ligação com alguns tipos de anomalias diagnosticadas no cérebro, por exemplo, epilepsia, mal de Parkinson e Alzheimer. Neste trabalho, realizamos um estudo da aplicação dos gráficos de recorrência, em sua versão espacial, na caracterização da coexistência de estados coerentes e incoerentes em sistemas dinâmicos acoplados. Utilizamos um modelo constituído de osciladores de fase para uma primeira abordagem da matriz de recorrência. Nossos resultados indicam que os diagnósticos quantitativos, baseados no gráfico de recorrência, detectam não só a existência de estados quimera como também estados sincronizados e dessincronizados que por ventura emergem na rede. Sobre esse aspecto, mostramos que a análise via recorrência espacial é superior à utilização do parâmetro de ordem global pós-colapso de estados quimera. Este cenário ocorre em algumas situações onde a rede exibe quimera e esta subitamente desaparece do sistema, que passa a exibir um comportamento sincronizado na frequência de seus osciladores. Neste caso, o parâmetro de ordem global não identifica esta mudança de comportamento sendo necessário uma interpretação via outro diagnóstico. Também utilizamos a rede de conectividade cortical de gato, como forma de acoplamento, e distinguimos duas formas de estados híbridos: uma quimera com a região incoerente em dinâmica temporal de spikes e outra quimera onde a região incoerente apresenta dinâmica temporal de bursts. Identificamos que este último caso de estados quimera possui maior robustez com relação à perturbação externa aplicada no sistema.Concluímos que a região de quimera com bursts necessita de uma intensidade de perturbação duas vezes superior que a região de spikes para deixar de existir na rede de neurônios

Le milieu marin est insonifié par une grand variété de sources acoustiques, qui peuventêtre monitorées par des enregistreurs acoustiques passifs autonomes. Parmi les sons enregistrés, ontrouve un grand nombre de signaux transitoires (signaux éphémères de durée courte), auxquelsappartiennent notamment les signaux impulsionnels que nous étudions dans cette thèse. Les signauximpulsionnels ont des propriétés spécifiques, telles que leur durée très courte (<1ms), leur faiblenombre d’oscillations, leur forte directivité, qui les rendent difficiles à étudier avec les outils detraitement du signal traditionnels (transformée de Fourier, autocorrélation, etc.).Dans un premier temps, nous nous intéressons à la détection des sources qui émettent des sériesd’impulsions rythmées (dauphins, cachalots, bélugas). Cette détection, s’appuie uniquement surles temps d’arrivée des impulsions reçues, pour effectuer une analyse du rythme au moyen d’uneautocorrélation complexe, et construire une représentation temps-rythme, permettant : i) de détecterles rythmes, ii) de connaître les temps de début et fin des émissions rythmées, iii) de connaître lavaleur du rythme et son évolution.Dans un second temps, nous étudions le potentiel d’une technique appelée analyse par récurrence desphases, pour caractériser les formes d’onde des impulsions. Après avoir présenté le cadre général decette méthode d’analyse, nous l’utilisons dans trois chaînes de traitement répondant à chacune destâches suivantes : i) détection des transitoires, ii) caractérisation et reconnaissance des transitoires,iii) estimation des différences des temps d’arrivée des transitoires sur deux capteurs.Toutes les méthodes développées dans cette étude ont été testées et validées sur des données simuléeset sur des données réelles acquises en mer / The underwater environment is insonified by a wide variety of acoustic sourcesthat can be monitored by autonomous passive acoustic recorders. A large number of the recordedsounds are transient signals (short-finite duration signals), among which the pulse signals that westudy in this thesis. Pulse signals have specific properties, such as a very short duration (<1ms), fewoscillations, a high directivity, which make them difficult to study by classical signal processing tools(Fourier transform, autocorrelation).In the first part of this study, we develop a method to detect sound sources emitting rhythmic pulsetrains (dolphins, sperm whales, beluga whales). This detector uses only the time of arrival of pulses atthe hydrophone to perform a rhythm analysis based on a complex autocorrelation and a time-rhythmrepresentation. This allows : i) to detect rhythmic pulse trains, ii) to know the beginning and endingtimes of pulse trains, iii) to know the value of the rhythm.In the second part of this thesis, we study the potential of a method called Recurrence Plot Analysis tocharacterize waveforms of pulse signals. After a general presentation of this method we develop threesignal processing architectures based on it, to perform the following tasks : i) transient detection, ii)transient characterization and pattern recognition, iii) estimation of time difference of arrival of thetransient on two hydrophones.All the methods developped in this thesis are validated on simulated and real data recorded at sea.

La déformation des signaux au long de leur trajet de propagation est un des plus importants facteurs qui doivent être considérés à la réception. Ces effets sont dus à des phénomènes comme l’atténuation, la réflexion, la dispersion et le bruit. Alors que les premiers deux phénomènes sont assez facile à surveiller, parce qu’elles affectent l’amplitude, respectivement le retard des signaux, les deux derniers phénomènes sont plus difficiles à contrôler, parce qu’elles changent les paramètres du signal (amplitude, fréquence et phase) de manière totalement dépendante de l’environnement.Dans cette thèse, l’objectif principal est de contribuer à l’analyse des signaux liés aux différents phénomènes physiques, en visant une meilleure compréhension de ces phénomènes, ainsi que l’estimation de leurs paramètres qui sont intéressants de point de vue applicatif. Plusieurs contextes applicatifs ont été investigués dans deux configurations de : active et passive.Pour la configuration active, le premier contexte applicatif consiste en l’étude du phénomène de cavitation dans le domaine de la surveillance de systèmes hydrauliques. La deuxième application de la configuration active est la détection et le suivi des objets immergés sans synchronisation entre les capteurs d’émission et de réception.Pour la configuration passive, nous nous concentrons sur l’analyse des transitoires de pression dans les conduites d’eau en utilisant une méthode non-intrusive ainsi que sur la surveillance des réseaux d’énergie électrique en présence des phénomènes transitoires comme les arcs électriques.Malgré les différences entre les considérations physiques spécifiques à ces applications, nous proposons un modèle mathématique unique pour les signaux issus des deux types de configurations. Le modèle est basé sur l’analyse des récurrences. Avec ce concept, nous proposons une nouvelle approche pour les ondes basées sur l’espace des phases. Cette technique de construction des formes d’ondes présente l’intérêt de conduire à des méthodes de d’investigation active à haut cadence, très utiles pour la surveillance des phénomènes dynamiques.En plus, nous proposons des approches nouvelles pour l’investigation des caractéristiques des signaux. La première est la mesure TDR* (Time Distributed Recurrences) qui quantifie la matrice des récurrences/ distances et qui est utilisée pour la détection des signaux transitoires. La deuxième approche est l’analyse des phases à plusieurs retards et elle est utilisée pour la discrimination entre des signaux avec des paramètres très proches. Finalement, la quantification des lignes diagonales de la matrice des récurrences est proposée comme alternative pour l’analyse des signaux modulés en fréquence.Les travaux présentent les résultats expérimentaux en utilisant les méthodes théorétiques proposées dans cette thèse. Les résultats sont comparés avec des techniques classiques.Des perspectives de ces travaux, tant dans les domaines théorique et qu’applicatif, sont discutés à la fin du mémoire. / Signals’ deformation along their propagation path is among the most important aspect which has to be taken into account at reception. These effects are caused by phenomena like attenuation, reflection, dispersion and noise. Whereas the first two are rather easy to monitor, because they affect the amplitude, respectively the delay, the latter two are more difficult to control, because they change signals’ parameters (amplitude, frequency and phase) in an environment-dependent manner.In this thesis, the main objective is to contribute to the analysis of signals related to different physical phenomena, aiming to better understand them as well as to estimate their parameters that are interesting from application point of view. Different applicative contexts have been investigated in active and passive sensing configurations. For the active part, we mention the monitoring of cavitation phenomena and its characterization for hydraulic system surveillance. The second application of the active sensing is the underwater object detection and tracking without synchronization between sensors. For the passive configuration, we focus on the pressure transient analysis in water pipes investigation with a non-intrusive method and on the surveillance of electrical power systems in the presence of transient phenomena such as electrical arcs.Despite the differences between the physical considerations, we propose a unique mathematical model of the signals issued from the active/passive sensing system used to analyze the considered phenomena. This model is based on the Recurrence Plot Analysis (RPA) method. With this concept, we propose the phase-space based waveform design. This waveform design technique presents the interest to conduct to a high speed sensing methods, very useful to monitor dynamic phenomena.Moreover, we propose new tools for the investigation of the signals characteristics. The first one is the TDR* measure (Time Distributed Recurrences) that quantifies the recurrence/ distance matrix and it is used for the detection of transient signals. The second one is the multi-lag phase analysis using multiple lags and it is successfully used to discriminate between signals with close parameters. Finally, the diagonal lines quantification of RPA matrix is proposed as an alternative for the analysis of modulated signals.Our work presents the experimental results using the proposed theoretical methods introduced by this thesis. The results are compared with classical techniques.The perspectives of this thesis are presented at the end of this paper.