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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
51

Blind dereverberation of speech from moving and stationary speakers using sequential Monte Carlo methods

Evers, Christine January 2010 (has links)
Speech signals radiated in confined spaces are subject to reverberation due to reflections of surrounding walls and obstacles. Reverberation leads to severe degradation of speech intelligibility and can be prohibitive for applications where speech is digitally recorded, such as audio conferencing or hearing aids. Dereverberation of speech is therefore an important field in speech enhancement. Driven by consumer demand, blind speech dereverberation has become a popular field in the research community and has led to many interesting approaches in the literature. However, most existing methods are dictated by their underlying models and hence suffer from assumptions that constrain the approaches to specific subproblems of blind speech dereverberation. For example, many approaches limit the dereverberation to voiced speech sounds, leading to poor results for unvoiced speech. Few approaches tackle single-sensor blind speech dereverberation, and only a very limited subset allows for dereverberation of speech from moving speakers. Therefore, the aim of this dissertation is the development of a flexible and extendible framework for blind speech dereverberation accommodating different speech sound types, single- or multiple sensor as well as stationary and moving speakers. Bayesian methods benefit from – rather than being dictated by – appropriate model choices. Therefore, the problem of blind speech dereverberation is considered from a Bayesian perspective in this thesis. A generic sequential Monte Carlo approach accommodating a multitude of models for the speech production mechanism and room transfer function is consequently derived. In this approach both the anechoic source signal and reverberant channel are estimated using their optimal estimators by means of Rao-Blackwellisation of the state-space of unknown variables. The remaining model parameters are estimated using sequential importance resampling. The proposed approach is implemented for two different speech production models for stationary speakers, demonstrating substantial reduction in reverberation for both unvoiced and voiced speech sounds. Furthermore, the channel model is extended to facilitate blind dereverberation of speech from moving speakers. Due to the structure of measurement model, single- as well as multi-microphone processing is facilitated, accommodating physically constrained scenarios where only a single sensor can be used as well as allowing for the exploitation of spatial diversity in scenarios where the physical size of microphone arrays is of no concern. This dissertation is concluded with a survey of possible directions for future research, including the use of switching Markov source models, joint target tracking and enhancement, as well as an extension to subband processing for improved computational efficiency.
52

Borne de Cramér-Rao déterministe pour l'analyse des performances asymptotiques en estimation d'un radar actif

Menni, Tarek 17 September 2012 (has links) (PDF)
L'émergence des formes d'onde numériques en radar et l'engouement de la communauté scientifique pour leur versatilité éprouvée en télécom, soulèvent naturellement chez les ingénieurs radaristes la question de l'amélioration effective des performances opérationnelles par ces nouvelles formes d'onde, notamment en matière de haute-résolution. Les travaux publiés sur le sujet sont prometteurs, à ceci près qu'ils sont le plus souvent basés sur des modèles théoriques un peu éloignés de la réalité opérationnelle ou sur des scénarios simplistes relativement à la capacité haute résolution envisagée (par exemple le faible nombre de sources pris en compte). En effet la prise en compte d'un modèle d'observation réaliste (large bande, à fréquence d'échantillonnage élevée) et de scénario à grand nombre de contributeurs conduit à des estimateurs dont la complexité d'implémentation n'est pas compatible des puissances de calcul actuelles. Une approche alternative, et compatible des puissances de calcul actuelles, pour la qualification des performances haute résolution est l'utilisation des bornes inférieures d'estimation, principalement la borne de Cramèr-Rao déterministe. L'examen de la littérature courante (notamment les monographies de référence) sur la borne de Cramèr-Rao déterministe a fait apparaître des lacunes relatives à sa formulation dans le contexte radar qui nous intéresse, à savoir MIMO large bande, multisources, multiparamètres à observations multiples. En effet dans la littérature courante, les observations multiples sont définies comme des réalisations multiples indépendantes d'un même modèle d'observation, alors qu'en radar il s'agit en général de la combinaison de modèles d'observation différents (variation de la forme d'onde). Ce constat a motivé l'essentiel de ce travail, à savoir l'établissement d'une expression analytique générale de la borne de Cramèr-Rao déterministe MIMO large bande, multisources, multiparamètres à modèles d'observations multiples pour la qualification (asymptotique) des performances en estimation d'un radar actif. Ce travail fournit un outil de comparaison des performances haute-résolution des différentes formes d'onde, dont les nouvelles formes d'onde numériques. De façon générale, l'expression analytique générale de la borne de Cramèr-Rao obtenue fournit la base théorique pour le développement des futurs radars à haute résolution.
53

Arklių lėtinė obstrukcinė plaučių liga. Kraujo ląstelių morfologijos bei kraujo dujų tyrimų rezultatų įvertinimas prieš ir po aerozolinės terapijos taikymo ultragarsiniu inhaliatoriumi / Equine recurrent airway obstruction. Blood cells morphology and blood gas evaluations before and after aerosol therapy with ultrasound nebuliser

Norvaišaitė, Jurgita 05 March 2014 (has links)
Aerozolinė terapija, lėtine obstrukcine plaučių liga sergantiems arkliams, nėra labai dažnai taikomas gydymo būdas Lietuvoje, tačiau ši terapija yra plačiai taikoma kitose šalyse. Aerozolinė terapija yra efektyvus arklių lėtinės obstrukcinės plaučių ligos gydymo būdas. Darbo tikslas: Šio darbo tikslas yra nustatyti bronchus plečiančių preparatų, kaip salbutamolio ir gliukokortikoidų preparatų, kaip deksametazono, aerozolinės terapijos įtaką, lėtine obstrukcine plaučių liga sergančių arklių kraujo dujoms ir kraujo ląstelių morfologijai. Metodai: Tyrimui buvo atrinkti šeši arkliai, kurių amžius yra nuo 5 iki 18 metų. Visi arkliai buvo laikomi vienodomis sąlygomis. Arkliai buvo suskirstyti į dvi grupes: į pirmąją grupę buvo atrinkti trys arkliai (n=3), su klinikiniais lėtinės obstrukcinės plaučių ligos simptomais. Visiems pirmojoje grupėje esantiems arkliams anksčiau buvo diagnozuota lėtinė obstrukcinė plaučių liga. Į kontrolinę grupę buvo atrinkti trys sveiki arkliai (n=3), kuriems niekada nebuvo pasireiškusios kvėpavimo takų ligos. Aerozolinė terapija buvo taikoma vieną kartą per dieną, septynias dienas iš eilės. Pirmiausia buvo inhaliuojamas salbutamolis, o tada - deksametazonas. Kontrolinės grupės arkliai nebuvo gydomi. Kraujo tyrimai pirmosios grupės arkliams buvo imami prieš taikant aerozolinę terapiją ir po septynių dienų aerozolinės terapijos taikymo. Antrosios grupės arkliams kraujo tyrimai buvo imami vieną kartą. Kraujo dujų tyrimas buvo atliekamas iš karto po... [toliau žr. visą tekstą] / Equine aerosol therapy for treating recurrent airway disease in horses is not a very common therapy used in Lithuania, but it is widely used in other countries. It is a very effective way of treating horses in crisis with reccurent airway disease. Aim of the study: The aim of this study was to establish, how the results of blood gas and blood cell morphology change after an aerosol bronchodilator such as salbutamol and the use of glucocorticoid such as dexamethazone for therapy on horses with recurrent airway disease. Methods: There were six horses in this study, 5 - 18 years of age, and they were kept under the same conditions. The horses were divided into two groups: the first group was made up of three horses (n = 3), previously diagnosed with recurrent airway disease. At the time of the study they had clinical signs of the disease. The control group were also made up of three horses (n = 3), who have never been diagnosed with respiratory diseases. Horses from the first group, were treated with aerosol salbutamol and dexamethasone for a week, once a day, with an ultrasound nebulizer. Horses from the control group were not treated. Blood samples from the horses of the first group were taken before aerosol therapy and after a one week period of therapy blood samples were drawn again for comparison. Blood samples from the control group were taken once. Blood gas tests were carried out with an Epoc blood analyzer and blood cell morphology was carried out with Abacus... [to full text]
54

Analysis of the modified Cramer Rao bound for burst mode symbol clock synchronisation

Doan, John January 2007 (has links)
This thesis presents an analysis of the Modified Cramer Rao Bound (MCRB) for synchroniser performance in burst mode communication applications. This is accomplished by introducing the topic of burst mode communications and its practical applications, discussing the importance of synchronisation, presenting a model through which the mathematical analysis of this thesis is based upon, deriving a set of equations which can be used to calculate the MCRB and finally by performing various calculations of the MCRB with different parameters to examine their effects on the MCRB. The methods presented in this thesis are different from those presented in existing literature, which generally do not address the issue of burst mode synchronisation directly. The differences between the methods presented in this thesis and those of existing literature is also discussed.
55

Segmented DP-SLAM

Maffei, Renan de Queiroz January 2013 (has links)
Localização e Mapeamento Simultâneos (SLAM) é uma das tarefas mais difíceis em robótica móvel, uma vez que existe uma dependência mútua entre a estimativa da localização do robô e a construção do mapa de ambiente. As estratégias de SLAM mais bem sucedidas focam na construção de um mapa métrico probabilístico empregando técnicas de filtragem Bayesiana. Embora tais métodos permitam a construção de soluções localmente consistentes e coerentes, o SLAM continua sendo um problema crítico em operações em ambientes grandes. Para contornar esta limitação, muitas estratégias dividem o ambiente em pequenas regiões, e formulam o problema de SLAM como uma combinação de múltiplos submapas métricos precisos associados em um mapa topológico. Este trabalho propõe um método de SLAM baseado nos algoritmos DP-SLAM (Distributed Particle SLAM) e SegSlam (Segmented SLAM). SegSLAM é um algoritmo que cria múltiplos submapas para cada região do ambiente, e posteriormente constrói o mapa global selecionando combinações de submapas. Por sua vez, DP-SLAM é um algoritmo de filtro de particulas Rao-Blackwellized que utiliza uma representação distribuída eficiente dos mapas das partículas, juntamente com a árvore de ascendência das partículas. A característica distribuída destas estruturas é favorável para a combinação de diferentes segmentos de mapa localmente precisos, o que aumenta a diversidade de soluções. O algoritmo proposto nesta dissertação, chamado SDP-SLAM, segmenta e combina diferentes hipóteses de trajetórias do robô, a fim de reconstruir o mapa do ambiente. Nossas principais contribuições são o desenvolvimento de novas estratégias para o casamento de submapas e para a estimativa de boas combinações de submapas. O SDP-SLAM foi avaliado através de experimentos realizados por um robô móvel operando em ambientes reais e simulados. / Simultaneous Localization and Mapping (SLAM) is one of the most difficult tasks in mobile robotics, since there is a mutual dependency between the estimation of the robot pose and the construction of the environment map. Most successful strategies in SLAM focus in building a probabilistic metric map employing Bayesian filtering techniques. While these methods allow the construction of consistent and coherent local solutions, the SLAM remains a critical problem in operations within large environments. To circumvent this limitation, many strategies divide the environment in small regions, and formulate the SLAM problem as a combination of multiple precise metric submaps associated in a topological map. This work proposes a SLAM method based on the Distributed Particle SLAM (DPSLAM) and the Segmented SLAM (SegSLAM) algorithms. SegSLAM is an algorithm that generates multiple submaps for every region of the environment, and then build the global map by selecting combinations of submaps. DP-SLAM is a Rao-Blackwellized particle filter algorithm that uses an efficient distributed representation of the particles maps associated with an ancestry tree of the particles. The distributed characteristic of these structures favors the combination of locally accurate map segments, that can increase the diversity of global level solutions. The algorithm proposed in this dissertation, called SDP-SLAM, segments and combines different hypotheses of robot trajectories to reconstruct the environment map. Our main contributions are the development of novel strategies for the matching of submaps and for the estimation of good submaps combinations. SDP-SLAM was evaluated through experiments performed by a mobile robot operating in real and simulated environments.
56

Segmented DP-SLAM

Maffei, Renan de Queiroz January 2013 (has links)
Localização e Mapeamento Simultâneos (SLAM) é uma das tarefas mais difíceis em robótica móvel, uma vez que existe uma dependência mútua entre a estimativa da localização do robô e a construção do mapa de ambiente. As estratégias de SLAM mais bem sucedidas focam na construção de um mapa métrico probabilístico empregando técnicas de filtragem Bayesiana. Embora tais métodos permitam a construção de soluções localmente consistentes e coerentes, o SLAM continua sendo um problema crítico em operações em ambientes grandes. Para contornar esta limitação, muitas estratégias dividem o ambiente em pequenas regiões, e formulam o problema de SLAM como uma combinação de múltiplos submapas métricos precisos associados em um mapa topológico. Este trabalho propõe um método de SLAM baseado nos algoritmos DP-SLAM (Distributed Particle SLAM) e SegSlam (Segmented SLAM). SegSLAM é um algoritmo que cria múltiplos submapas para cada região do ambiente, e posteriormente constrói o mapa global selecionando combinações de submapas. Por sua vez, DP-SLAM é um algoritmo de filtro de particulas Rao-Blackwellized que utiliza uma representação distribuída eficiente dos mapas das partículas, juntamente com a árvore de ascendência das partículas. A característica distribuída destas estruturas é favorável para a combinação de diferentes segmentos de mapa localmente precisos, o que aumenta a diversidade de soluções. O algoritmo proposto nesta dissertação, chamado SDP-SLAM, segmenta e combina diferentes hipóteses de trajetórias do robô, a fim de reconstruir o mapa do ambiente. Nossas principais contribuições são o desenvolvimento de novas estratégias para o casamento de submapas e para a estimativa de boas combinações de submapas. O SDP-SLAM foi avaliado através de experimentos realizados por um robô móvel operando em ambientes reais e simulados. / Simultaneous Localization and Mapping (SLAM) is one of the most difficult tasks in mobile robotics, since there is a mutual dependency between the estimation of the robot pose and the construction of the environment map. Most successful strategies in SLAM focus in building a probabilistic metric map employing Bayesian filtering techniques. While these methods allow the construction of consistent and coherent local solutions, the SLAM remains a critical problem in operations within large environments. To circumvent this limitation, many strategies divide the environment in small regions, and formulate the SLAM problem as a combination of multiple precise metric submaps associated in a topological map. This work proposes a SLAM method based on the Distributed Particle SLAM (DPSLAM) and the Segmented SLAM (SegSLAM) algorithms. SegSLAM is an algorithm that generates multiple submaps for every region of the environment, and then build the global map by selecting combinations of submaps. DP-SLAM is a Rao-Blackwellized particle filter algorithm that uses an efficient distributed representation of the particles maps associated with an ancestry tree of the particles. The distributed characteristic of these structures favors the combination of locally accurate map segments, that can increase the diversity of global level solutions. The algorithm proposed in this dissertation, called SDP-SLAM, segments and combines different hypotheses of robot trajectories to reconstruct the environment map. Our main contributions are the development of novel strategies for the matching of submaps and for the estimation of good submaps combinations. SDP-SLAM was evaluated through experiments performed by a mobile robot operating in real and simulated environments.
57

Failure and Degradation Modes of PV modules in a Hot Dry Climate: Results after 16 years of field exposure

January 2013 (has links)
abstract: This study evaluates two 16 year old photovoltaic power (PV) plants to ascertain degradation rates and various failure modes which occur in a "hot-dry" climate. The data obtained from this study can be used by module manufacturers in determining the warranty limits of their modules and also by banks, investors, project developers and users in determining appropriate financing or decommissioning models. In addition, the data obtained in this study will be helpful in selecting appropriate accelerated stress tests which would replicate the field failures for the new modules and would predict the lifetime for new PV modules. The two power plants referred to as Site 4A and -4B with (1512 modules each) were initially installed on a single axis tracking system in Gilbert, Arizona for the first seven years and have been operating at their current location in Mesa, Arizona for the last nine years at fixed horizontal tilt Both sites experience hot-dry desert climate. Average degradation rate is 0.85%/year for the best modules and 1.1%/year for all the modules (excluding the safety failed modules). Primary safety failure mode is the backsheet delamination though it is small (less than 1.7%). Primary degradation mode and reliability failure mode may potentially be attributed to encapsulant browning leading to transmittance/current loss and thermo-mechanical solder bond fatigue (cell-ribbon and ribbon-ribbon) leading to series resistance increase. Average soiling loss of horizontal tilt based modules is 11.1%. About 0.5-1.7% of the modules qualify for the safety returns under the typical 20/20 warranty terms, 73-76% of the modules qualify for the warranty claims under the typical 20/20 power warranty terms and 24-26% of the modules are meeting the typical 20/20 power warranty terms. / Dissertation/Thesis / M.S.Tech Engineering 2013
58

Segmented DP-SLAM

Maffei, Renan de Queiroz January 2013 (has links)
Localização e Mapeamento Simultâneos (SLAM) é uma das tarefas mais difíceis em robótica móvel, uma vez que existe uma dependência mútua entre a estimativa da localização do robô e a construção do mapa de ambiente. As estratégias de SLAM mais bem sucedidas focam na construção de um mapa métrico probabilístico empregando técnicas de filtragem Bayesiana. Embora tais métodos permitam a construção de soluções localmente consistentes e coerentes, o SLAM continua sendo um problema crítico em operações em ambientes grandes. Para contornar esta limitação, muitas estratégias dividem o ambiente em pequenas regiões, e formulam o problema de SLAM como uma combinação de múltiplos submapas métricos precisos associados em um mapa topológico. Este trabalho propõe um método de SLAM baseado nos algoritmos DP-SLAM (Distributed Particle SLAM) e SegSlam (Segmented SLAM). SegSLAM é um algoritmo que cria múltiplos submapas para cada região do ambiente, e posteriormente constrói o mapa global selecionando combinações de submapas. Por sua vez, DP-SLAM é um algoritmo de filtro de particulas Rao-Blackwellized que utiliza uma representação distribuída eficiente dos mapas das partículas, juntamente com a árvore de ascendência das partículas. A característica distribuída destas estruturas é favorável para a combinação de diferentes segmentos de mapa localmente precisos, o que aumenta a diversidade de soluções. O algoritmo proposto nesta dissertação, chamado SDP-SLAM, segmenta e combina diferentes hipóteses de trajetórias do robô, a fim de reconstruir o mapa do ambiente. Nossas principais contribuições são o desenvolvimento de novas estratégias para o casamento de submapas e para a estimativa de boas combinações de submapas. O SDP-SLAM foi avaliado através de experimentos realizados por um robô móvel operando em ambientes reais e simulados. / Simultaneous Localization and Mapping (SLAM) is one of the most difficult tasks in mobile robotics, since there is a mutual dependency between the estimation of the robot pose and the construction of the environment map. Most successful strategies in SLAM focus in building a probabilistic metric map employing Bayesian filtering techniques. While these methods allow the construction of consistent and coherent local solutions, the SLAM remains a critical problem in operations within large environments. To circumvent this limitation, many strategies divide the environment in small regions, and formulate the SLAM problem as a combination of multiple precise metric submaps associated in a topological map. This work proposes a SLAM method based on the Distributed Particle SLAM (DPSLAM) and the Segmented SLAM (SegSLAM) algorithms. SegSLAM is an algorithm that generates multiple submaps for every region of the environment, and then build the global map by selecting combinations of submaps. DP-SLAM is a Rao-Blackwellized particle filter algorithm that uses an efficient distributed representation of the particles maps associated with an ancestry tree of the particles. The distributed characteristic of these structures favors the combination of locally accurate map segments, that can increase the diversity of global level solutions. The algorithm proposed in this dissertation, called SDP-SLAM, segments and combines different hypotheses of robot trajectories to reconstruct the environment map. Our main contributions are the development of novel strategies for the matching of submaps and for the estimation of good submaps combinations. SDP-SLAM was evaluated through experiments performed by a mobile robot operating in real and simulated environments.
59

Método adaptativo de Markov Chain Monte Carlo para manipulação de modelos Bayesianos

FIRMINO, Paulo Renato Alves 31 January 2009 (has links)
Made available in DSpace on 2014-06-12T17:35:07Z (GMT). No. of bitstreams: 2 arquivo3632_1.pdf: 1762777 bytes, checksum: e94374ad230aa9afab9b590aa9caa2bd (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Ao longo dos anos, modelos Bayesianos vêm recebendo atenção especial da academia e em aplicações principalmente por possibilitarem uma combinação matemática entre corpos de evidência subjetiva e empírica. A metodologia de integração de Monte Carlo via cadeias de Markov é uma das principais classes de algoritmos para computar estimativas marginais a partir de modelos Bayesianos. Entre os métodos de integração de Monte Carlo via cadeias de Markov, o algoritmo de Metropolis-Hastings merece destaque. Em resumo, para o conjunto de d variáveis (ou componentes) do modelo Bayesiano, X = (X1, X2, , Xd), tal algoritmo elabora uma cadeia de Markov onde cada estado visitado é uma realização de X, x = (x1, x2, , xd), amostrada das distribuições de probabilidades condicionais das variáveis do modelo, f(xi| x1, x2, , xi-1, xi+1, , xd). Quando a simulação é governada por distribuições cuja amostragem direta é viável, o algoritmo de Metropolis-Hastings converge para o método de Gibbs e técnicas de redução de variância tais como Rao-Blackwellization podem ser adotadas. Caso contrário, diante de distribuições cuja amostragem direta é inviável, Rao-Blackwellization é possível a partir do método de griddy-Gibbs, que recorre a funções aproximadas. Esta tese propõe uma variante de griddy-Gibbs que pode ser também classificada como uma extensão do algoritmo de Metropolis-Hastings (diferentemente do método de griddy-Gibbs tradicional que descarta a possibilidade de se rejeitar os valores amostrados ao longo das simulações). Além disso, algoritmos de integração numérica adaptativos e técnicas de agrupamento, tais como o método adaptativo de Simpson e centroidal Voronoi tessellations, são adotados. Casos de estudo apontam o algoritmo proposto como uma boa alternativa a métodos existentes, promovendo estimativas mais precisas sob um menor consumo de recursos computacionais em muitas situações
60

Uma melhora das cotas de Feng-Rao e de Miura para a distância mínima de códigos definidos sobre uma variedade afim

MESQUITA, Aline Mota de 18 December 2007 (has links)
Made available in DSpace on 2014-07-29T16:02:21Z (GMT). No. of bitstreams: 1 Dissertacao Aline.pdf: 730328 bytes, checksum: 01d446325586d61a96fd84af4b10cdb5 (MD5) Previous issue date: 2007-12-18 / In this work we present some linear codes and we discuss about parameters of cyclic codes families that lead to the characterization of the Goppa codes, which we describe minimum distance bounds when it is given for an affine variety. When this code is defined like this, we say that it is an improved geometric Goppa code. The first bounds mentioned in this work was given by Feng and Rao in [6] (Feng-Rao bound), later improved by Miura in [18],[19] (weakly Feng-Rao bound), that in its turn has been improved by G. Salazar, D. Dunn and S. B. Graham in [22] (advisory bound and strong advisory estimate). This work was based in this last article. We finishing the dissertation showing families of codes for which we verified the veracity of the improvement of bounds. / Nesta dissertação apresentamos alguns códigos lineares e tratamos de parâmetros de famílias de cóodigos clicos que conduzem á caracterização dos códigos de Goppa, para o qual descrevemos cotas para a distância mínima quando este é dado sobre uma variedade afm. Quando tal código é assim defnido, dizemos que ele é um código geométrico de Goppa melhorado. A primeira das cotas mencionada neste trabalho foi dada por Feng e Rao em [6] (cota de Feng-Rao), posteriormente melhorada por Miura em [18],[19] (cota fraca de Feng-Rao), que por sua vez foi melhorada por G. Salazar, D. Dunn e S. B. Graham em [22] (cota indicativa e estimativa indicativa forte), sendo que neste último artigo está fundamentada esta dissertação. Encerramos nosso trabalho exibindo famílias de códigos para as quais verificamos a veracidade das melhoras das cotas.

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