Le cerveau endormi tend à se déconnecter dans sa progression vers le sommeil lent (SL) chez les jeunes adultes et se déconnecte moins chez les plus âgés. Les ondes lentes (OL) sont les caractéristiques principales du sommeil lent sur l’électroencéphalogramme (EEG). Notre groupe a récemment montré que deux types d’OL co-existent, les « slow switcher » (SlowS) et les « fast switcher » (FastS), caractérisées par leur vitesse de transition entre les maximums d’hyperpolarisation et de dépolarisation. Sur l’EEG, la connectivité globale pendant la transition des SlowS et des FastS diffère et diminue avec le vieillissement. Dans cette étude, nous utilisons des enregistrements de magnétoencéphalographie pour évaluer les changements relatifs à l’âge sur les générateurs des OL pendant la transition entre les maximums d’hyperpolarisation et de dépolarisation en termes de 1) topographie et 2) connectivité, avec l’indice de délais de phase pondéré basé sur le délai de phase moyen dans la transition des OL. Nous avons fait l’hypothèse que comparativement aux OL des individus jeunes, les OL des individus plus âgés vont 1) impliquer des régions corticales plus étendues et 2) montrer plus de connectivité, spécialement pour les SlowS. Nos résultats révèlent que comparativement aux jeunes participants, les plus vieux montrent 1) plus d’implication du précuneus droit pendant les SlowS et 2) une connectivité globale supérieure, surtout pour les SlowS. Finalement, les individus plus jeunes montrent plus de connectivité que les individus plus âgés entre des régions spécifiques, plus précisément dans le réseau antéropostérieur pour les SlowS que les FastS. Ensemble, nos résultats suggèrent une perte de flexibilité des réseaux pendant la transition des OL chez les individus plus âgés par rapport aux individus plus jeunes. / The sleeping brain tends to disconnect as it progresses toward slow wave sleep (SWS) in young adults and disconnects less in older adults. Slow waves (SW) are the main characteristics of slow wave sleep on the electroencephalogram (EEG). Our group recently showed that two types of SW co-exist, the “slow switcher” (SlowS) and the “fast switcher” (FastS), characterized by the transition speed between the hyperpolarized and depolarized peaks. On the EEG, the global connectivity during the transition of the SlowS and FastS differs and is reduced with aging. In this study, we used magnetoencephalography recordings to investigate age-related differences on the SW generators during the transition between the hyperpolarized and depolarized peaks in terms of 1) topography and 2) connectivity, using the weighted phase lag index based on the average phase lag during the SW transition. We hypothesised that as compared to younger individuals, SW of older participants would 1) involve broader cortical areas and 2) show higher connectivity than younger individuals, particularly for the SlowS. Our results revealed that as compared to younger participants, older individuals showed 1) more involvement of the right precuneus during the SlowS and 2) globally higher connectivity, more significantly for the SlowS. Finally, younger individuals showed higher connectivity than older individuals between specific regions, more precisely in the anteroposterior network for the SlowS than the FastS. Altogether, our results suggest an impaired flexibility of the network during the SW transition in older individuals as compared to younger individuals.

The PAL (Practise and Learn) Original is a ball board consisting of three wooden boards placed in a triangle, developed to practise football players’ passing ability and first touch. The former Swedish international footballer Jessica Landström observed that these ball boards can, if they are improved, help footballers to develop even more skills while practicing alone. Landstr¨om’s idea was to put lamps on top off the ball boards which light up when a certain ball board expects to receive a pass. This would force the player to look up instead of looking at the ball and hence improve their vision. We concluded that speaking also is important within football. So our objective became to follow up on the development of the simple PAL Original to a ball board which rotates towards a sound source. We wanted to achieve this without configuring the PAL Original’s construction. With the purpose of executing the idea we needed to estimate the angle between a sound source and a face of the ball board, rotate the ball board with an electric motor, communicate wirelessly between units and detect a ball hit when the ball board receives a pass. The final prototype consists of two systems, one system executing the sound source localization and rotation and the other system executing the detection of ball hit and wireless communication. The first system uses time difference of arrival (TDOA) between incoming sound for three sound sensors to calculate an angle, which in turn is communicated to a DC motorthat executes the rotation. The other system combines an LED to light up when a pass is expected, an accelerometer to detect a pass, and radio transceivers to communicate with each other. When at least three of these devices are used a randomizing algorithm decides which one should light its LED next when the first one detects a pass. / PAL (Practice and Learn) Original är ett bollplank bestående av tre träskivor placerade i en triangel, utvecklad för att träna fotbollsspelares passningsförmåga och första touch. Jessica Landström, landslagsmeriterad fotbollsspelare, insåg att dessa bollplank kan utvecklas till att hjälpa fotbollsspelare att träna ännu fler områden vid indviduell träning. Landströms ursprungliga idé var att placera en lampa på bollplanket som lyser upp när den förväntar sig en passning, detta för att tvinga spelaren att titta upp istället för att titta på bollen, och därigenom träna spelarens spelförståelse. Vi drog slutsatsen att det också är mycket viktigt med kommunikation i fotboll. Vårt mål blev därför att vidareutveckla PAL Original till ett bollplank som roterar en sida mot en ljudkälla. Vi ville uppnå detta så att det är kompatibelt med PAL Original utan att ändra dess konstruktion. För att genomföra detta behövde vi alltså uppskatta vinkeln mellan en ljudkälla och en sida av det triangulära bollplanket, rotera bollplanket med en motor, kommunicera trådlöst och detektera när bollplanket mottar en passning. Den slutliga prototypen består av två system, ett system som utför lokalisering av ljudkälla samt rotation och ett system som utför detektering av bollträff samt hanterar trådlös kommunikation. Det första systemet utnyttjar tidsskillnad för ankomst, TDOA (Time Difference of Arrival), mellan inkommande ljud till tre ljudsensorer för att beräkna en vinkel, som i sin tur kommuniceras till en likströmsmotor som utför rotationen. Det andra systemet kombinerar en lysdiod som lyser när en passning förväntas, en accelerometer för att detektera att passning mottagits och radiosändare samt mottagare för trådlös kommunikation. När minst tre sådana enheter används, bestämmer en slumpgenerator vilken enhet som ska tända sin lysdiod när den första detekterar en passning.

The PAL (Practise and Learn) Original is a ball boardconsisting of three wooden boards placed in a triangle, developedto practise football players’ passing ability and firsttouch. The former Swedish international footballer JessicaLandstr¨om observed that these ball boards can, if they areimproved, help footballers to develop even more skills whilepracticing alone. Landstr¨om’s idea was to put lamps on topoff the ball boards which light up when a certain ball boardexpects to receive a pass. This would force the player tolook up instead of looking at the ball and hence improvetheir vision.We concluded that speaking also is important withinfootball. So our objective became to follow up on the developmentof the simple PAL Original to a ball board whichrotates towards a sound source. We wanted to achieve thiswithout configuring the PAL Original’s construction.With the purpose of executing the idea we needed toestimate the angle between a sound source and a face ofthe ball board, rotate the ball board with an electric motor,communicate wirelessly between units and detect a ball hitwhen the ball board receives a pass.The final prototype consists of two systems, one systemexecuting the sound source localization and rotation andthe other system executing the detection of ball hit andwireless communication.The first system uses time difference of arrival (TDOA)between incoming sound for three sound sensors to calculatean angle, which in turn is communicated to a DC motorthat executes the rotation.The other system combines an LED to light up whena pass is expected, an accelerometer to detect a pass, andradio transceivers to communicate with each other. Whenat least three of these devices are used a randomizing algorithmdecides which one should light its LED next whenthe first one detects a pass. / PAL (Practice and Learn) Original är ett bollplankbestående av tre träskivor placerade i en triangel, utveckladför att träna fotbollsspelares passningsförmåga och förstatouch. Jessica Landström, landslagsmeriterad fotbollsspelare,insåg att dessa bollplank kan utvecklas till att hjälpafotbollsspelare att träna ännu fler områden vid indviduellträning. Landströms ursprungliga idé var att placeraen lampa på bollplanket som lyser upp när den förväntarsig en passning, detta för att tvinga spelaren att titta uppistället för att titta på bollen, och därigenom träna spelarensspelförståelse.Vi drog slutsatsen att det också är mycket viktigt medkommunikation i fotboll. Vårt mål blev därför att vidareutvecklaPAL Original till ett bollplank som roterar en sidamot en ljudkälla. Vi ville uppnå detta så att det är kompatibeltmed PAL Original utan att ändra dess konstruktion.För att genomföra detta behövde vi alltså uppskattavinkeln mellan en ljudkälla och en sida av det triangulärabollplanket, rotera bollplanket med en motor, kommuniceratrådlöst och detektera när bollplanket mottar en passning.Den slutliga prototypen består av två system, ett systemsom utför lokalisering av ljudkälla samt rotation ochett system som utför detektering av bollträff samt hanterartrådlös kommunikation.Det första systemet utnyttjar tidsskillnad för ankomst,TDOA (Time Difference of Arrival), mellan inkommandeljud till tre ljudsensorer för att beräkna en vinkel, som i sintur kommuniceras till en likströmsmotor som utför rotationen.Det andra systemet kombinerar en lysdiod som lysernär en passning förväntas, en accelerometer för att detekteraatt passning mottagits och radiosändare samt mottagareför trådlös kommunikation. När minst tre sådana enheteranvänds, bestämmer en slumpgenerator vilken enhet somska tända sin lysdiod när den första detekterar en passning.

No description available.

Inhibitory control processes have intensively been studied in cognitive science for the past decades. Even though the neural dynamics underlying these processes are increasingly better understood, a critical open question is how the representational dynamics of the inhibitory control processes are modulated when engaging in response inhibition in a relatively automatic or a controlled mode. Against the background of an overarching theory of perception-action integration, we combine temporal and spatial EEG signal decomposition methods with multivariate pattern analysis and source localization to obtain fine-grained insights into the neural dynamics of the representational content of response inhibition. For this purpose, we used a sample of N = 40 healthy adult participants. The behavioural data suggest that response inhibition was better in a more controlled than a more automated response execution mode. Regarding neural dynamics, effects of response inhibition modes relied on a concomitant coding of stimulus-related information and rules of how stimulus information is related to the appropriate motor programme. Crucially, these fractions of information, which are encoded at the same time in the neurophysiological signal, are based on two independent spatial neurophysiological activity patterns, also showing differences in the temporal stability of the representational content. Source localizations revealed that the precuneus and inferior parietal cortex regions are more relevant than prefrontal areas for the representation of stimulus–response selection codes. We provide a blueprint how a concatenation of EEG signal analysis methods, capturing distinct aspects of neural dynamics, can be connected to cognitive science theory on the importance of representations in action control.

Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method. / Master of Science

Multichannel acoustic signal processing has undergone major development in recent years due to the increased complexity of current audio processing applications. People want to collaborate through communication with the feeling of being together and sharing the same environment, what is considered as Immersive Audio Schemes. In this phenomenon, several acoustic e ects are involved: 3D spatial sound, room compensation, crosstalk cancelation, sound source localization, among others. However, high computing capacity is required to achieve any of these e ects in a real large-scale system, what represents a considerable limitation for real-time applications. The increase of the computational capacity has been historically linked to the number of transistors in a chip. However, nowadays the improvements in the computational capacity are mainly given by increasing the number of processing units, i.e expanding parallelism in computing. This is the case of the Graphics Processing Units (GPUs), that own now thousands of computing cores. GPUs were traditionally related to graphic or image applications, but new releases in the GPU programming environments, CUDA or OpenCL, allowed that most applications were computationally accelerated in elds beyond graphics. This thesis aims to demonstrate that GPUs are totally valid tools to carry out audio applications that require high computational resources. To this end, di erent applications in the eld of audio processing are studied and performed using GPUs. This manuscript also analyzes and solves possible limitations in each GPU-based implementation both from the acoustic point of view as from the computational point of view. In this document, we have addressed the following problems: Most of audio applications are based on massive ltering. Thus, the rst implementation to undertake is a fundamental operation in the audio processing: the convolution. It has been rst developed as a computational kernel and afterwards used for an application that combines multiples convolutions concurrently: generalized crosstalk cancellation and equalization. The proposed implementation can successfully manage two di erent and common situations: size of bu ers that are much larger than the size of the lters and size of bu ers that are much smaller than the size of the lters. Two spatial audio applications that use the GPU as a co-processor have been developed from the massive multichannel ltering. First application deals with binaural audio. Its main feature is that this application is able to synthesize sound sources in spatial positions that are not included in the database of HRTF and to generate smoothly movements of sound sources. Both features were designed after di erent tests (objective and subjective). The performance regarding number of sound source that could be rendered in real time was assessed on GPUs with di erent GPU architectures. A similar performance is measured in a Wave Field Synthesis system (second spatial audio application) that is composed of 96 loudspeakers. The proposed GPU-based implementation is able to reduce the room e ects during the sound source rendering. A well-known approach for sound source localization in noisy and reverberant environments is also addressed on a multi-GPU system. This is the case of the Steered Response Power with Phase Transform (SRPPHAT) algorithm. Since localization accuracy can be improved by using high-resolution spatial grids and a high number of microphones, accurate acoustic localization systems require high computational power. The solutions implemented in this thesis are evaluated both from localization and from computational performance points of view, taking into account different acoustic environments, and always from a real-time implementation perspective. Finally, This manuscript addresses also massive multichannel ltering when the lters present an In nite Impulse Response (IIR). Two cases are analyzed in this manuscript: 1) IIR lters composed of multiple secondorder sections, and 2) IIR lters that presents an allpass response. Both cases are used to develop and accelerate two di erent applications: 1) to execute multiple Equalizations in a WFS system, and 2) to reduce the dynamic range in an audio signal. / Belloch Rodríguez, JA. (2014). PERFORMANCE IMPROVEMENT OF MULTICHANNEL AUDIO BY GRAPHICS PROCESSING UNITS [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/40651 / Premios Extraordinarios de tesis doctorales

L’imagerie acoustique est une technique performante pour la localisation et la reconstruction de puissance des sources acoustiques en utilisant des mesures limitées au réseau des microphones. Elle est largement utilisée pour évaluer l’influence acoustique dans l’industrie automobile et aéronautique. Les méthodes d’imagerie acoustique impliquent souvent un modèle direct de propagation acoustique et l’inversion de ce modèle direct. Cependant, cette inversion provoque généralement un problème inverse mal-posé. Par conséquent, les méthodes classiques ne permettent d’obtenir de manière satisfaisante ni une haute résolution spatiale, ni une dynamique large de la puissance acoustique. Dans cette thèse, nous avons tout d’abord nous avons créé un modèle direct discret de la puissance acoustique qui devient alors à la fois linéaire et déterminé pour les puissances acoustiques. Et nous ajoutons les erreurs de mesures que nous décomposons en trois parties : le bruit de fond du réseau de capteurs, l’incertitude du modèle causée par les propagations à multi-trajets et les erreurs d’approximation de la modélisation. Pour la résolution du problème inverse, nous avons tout d’abord proposé une approche d’hyper-résolution en utilisant une contrainte de parcimonie, de sorte que nous pouvons obtenir une plus haute résolution spatiale robuste à aux erreurs de mesures à condition que le paramètre de parcimonie soit estimé attentivement. Ensuite, afin d’obtenir une dynamique large et une plus forte robustesse aux bruits, nous avons proposé une approche basée sur une inférence bayésienne avec un a priori parcimonieux. Toutes les variables et paramètres inconnus peuvent être estimées par l’estimation du maximum a posteriori conjoint (JMAP). Toutefois, le JMAP souffrant d’une optimisation non-quadratique d’importants coûts de calcul, nous avons cherché des solutions d’accélération algorithmique: une approximation du modèle direct en utilisant une convolution 2D avec un noyau invariant. Grâce à ce modèle, nos approches peuvent être parallélisées sur des Graphics Processing Unit (GPU) . Par ailleurs, nous avons affiné notre modèle statistique sur 2 aspects : prise en compte de la non stationarité spatiale des erreurs de mesures et la définition d’une loi a priori pour les puissances renforçant la parcimonie en loi de Students-t. Enfin, nous ont poussé à mettre en place une Approximation Variationnelle Bayésienne (VBA). Cette approche permet non seulement d’obtenir toutes les estimations des inconnues, mais aussi de fournir des intervalles de confiance grâce aux paramètres cachés utilisés par les lois de Students-t. Pour conclure, nos approches ont été comparées avec des méthodes de l’état-de-l’art sur des données simulées, réelles (provenant d’essais en soufflerie chez Renault S2A) et hybrides. / Acoustic imaging is an advanced technique for acoustic source localization and power reconstruction using limited measurements at microphone sensor array. This technique can provide meaningful insights into performances, properties and mechanisms of acoustic sources. It has been widely used for evaluating the acoustic influence in automobile and aircraft industries. Acoustic imaging methods often involve in two aspects: a forward model of acoustic signal (power) propagation, and its inverse solution. However, the inversion usually causes a very ill-posed inverse problem, whose solution is not unique and is quite sensitive to measurement errors. Therefore, classical methods cannot easily obtain high spatial resolutions between two close sources, nor achieve wide dynamic range of acoustic source powers. In this thesis, we firstly build up a discrete forward model of acoustic signal propagation. This signal model is a linear but under-determined system of equations linking the measured data and unknown source signals. Based on this signal model, we set up a discrete forward model of acoustic power propagation. This power model is both linear and determined for source powers. In the forward models, we consider the measurement errors to be mainly composed of background noises at sensor array, model uncertainty caused by multi-path propagation, as well as model approximating errors. For the inverse problem of the acoustic power model, we firstly propose a robust super-resolution approach with the sparsity constraint, so that we can obtain very high spatial resolution in strong measurement errors. But the sparsity parameter should be carefully estimated for effective performance. Then for the acoustic imaging with large dynamic range and robustness, we propose a robust Bayesian inference approach with a sparsity enforcing prior: the double exponential law. This sparse prior can better embody the sparsity characteristic of source distribution than the sparsity constraint. All the unknown variables and parameters can be alternatively estimated by the Joint Maximum A Posterior (JMAP) estimation. However, this JMAP suffers a non-quadratic optimization and causes huge computational cost. So that we improve two following aspects: In order to accelerate the JMAP estimation, we investigate an invariant 2D convolution operator to approximate acoustic power propagation model. Owing to this invariant convolution model, our approaches can be parallelly implemented by the Graphics Processing Unit (GPU). Furthermore, we consider that measurement errors are spatially variant (non-stationary) at different sensors. In this more practical case, the distribution of measurement errors can be more accurately modeled by Students-t law which can express the variant variances by hidden parameters. Moreover, the sparsity enforcing distribution can be more conveniently described by the Student's-t law which can be decomposed into multivariate Gaussian and Gamma laws. However, the JMAP estimation risks to obtain so many unknown variables and hidden parameters. Therefore, we apply the Variational Bayesian Approximation (VBA) to overcome the JMAP drawbacks. One of the fabulous advantages of VBA is that it can not only achieve the parameter estimations, but also offer the confidential interval of interested parameters thanks to hidden parameters used in Students-t priors. To conclude, proposed approaches are validated by simulations, real data from wind tunnel experiments of Renault S2A, as well as the hybrid data. Compared with some typical state-of-the-art methods, the main advantages of proposed approaches are robust to measurement errors, super spatial resolutions, wide dynamic range and no need for source number nor Signal to Noise Ration (SNR) beforehand.

La localisation de source Distribuée Cohérente (DC) présente un défi du traitement d'antenne. Les contributions de cette thèse s’articulent principalement autour de trois aspects. Premièrement, un estimateur conjoint de l'angle, la distance, la dispersion et la forme de la source appelée JADSSE est proposé pour le cas champ proche. L’estimation d’un paramètre de forme de distribution de la dispersion permet d’éviter des erreurs de modèles sur l’a priori de la forme de la distribution. Deuxièmement, on généralise l'estimateur Decoupled DSPE en champ proche. Cette approche permet de découpler l'estimation de la Direction D’Arrivée (DDA) et de la distance de l'estimation de la dispersion. Afin de permettre l’estimation de la dispersion sans connaître a priori les formes de distribution, on propose le DADSSE qui consiste à estimer successivement la DDA, la distance et ensuite la dispersion et la forme de la distribution de la source. Troisièmement, on généralise le modèle DC avec une dispersion spatiale bidimensionnelle de la source ainsi que l’estimateur JADSSE. Deux approches sont proposées pour l’estimation de la puissance prenant en compte le modèle d’étalement des sources. Les méthodes proposées sont testées sur les données expérimentales de la soufflerie de Renault. Les résultats mettent en évidence des sources aéro-acoustiques proches et de faibles puissances. L’ensemble de ces travaux permet de fournir un outil pour une meilleure cartographie et caractérisation des sources aéro-acoustiques grâce à l’estimation de la position, l'étalement, la puissance et la forme. / Localization of Coherently Distributed (CD) source presents a challenge in the array signal processing. Our work motivates the localization of aero-acoustic source based on its spatial extension. This challenge is practically ignored in the literature of acoustic imaging field where many applications consist in mapping noisy source to reduce its contribution. The thesis presents the three following contributions. First, we propose a Joint Angle, Distance, Spread and Shape Estimator called JADSSE. The estimation of the so-called spread shape distribution parameter proposed by JADSSE avoids the modeling error due to the required a priori knowledge on the source shape when using classical estimators. Second, we expand the Decoupled DSPE to the near field. This method decouples the Direction of Arrival (DoA) and the range estimation from the spread estimation. Meanwhile, this method prevents the spread estimation for unknown shape distribution. Therefore, we propose the DADSSE to successively estimate the DOA, the range and then the spread and the shape distribution of the source. Third, we generalize the CD model and the JADSSE to consider the bi-dimensional spread of the source. Next, we propose two source power estimation approaches accounting the spatial spread of the source. The proposed methods are tested using a set of experimental data of the Renault wind tunnel application. Results show the presence of new aero-acoustic sources especially the overlapped ones with weak powers. We provide a tool to better map and characterize the aero-acoustic source by estimating the position, spread, power and shape.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Este trabalho se propÃe a investigar e propor diferentes tÃcnicas de estimaÃÃo de canal de mÃltiplas entradas e mÃltiplas saÃdas (MIMO) para sistemas de comunicaÃÃo multiusuÃrio operando em regime de interferÃncia em cenÃrio de mÃltiplas cÃlulas. AtenÃÃo particular à dada ao caso onde as estaÃÃes rÃdio-base sÃo equipadas com arranjos de antenas apresentando grande quantidade de antenas, configurando o que se tem referido na literatura como sistemas de comunicaÃÃo MIMO de grande dimensÃo (VL-MIMO, do inglÃs: very large MIMO). Algumas destas tÃcnicas exploram as propriedades das grandes matrizes aleatÃrias e sÃo menos afetadas pela contaminaÃÃo de pilotos. Nesta dissertaÃÃo, os parÃmetros do canal VL-MIMO sÃo estimados a partir de uma decomposiÃÃo em autovalores (EVD, do inglÃs: eigenvalue-decomposition) da matriz de covariÃncia na saÃda do arranjo de antenas receptoras. Esta tÃcnica se mostra menos sensÃvel à presenÃa de interferÃncia do que outras que nÃo exploram propriedades especÃficas da matriz de canal VL-MIMO, como à o caso da soluÃÃo clÃssica dos mÃnimos quadrados (LS, do inglÃs: least-squares). Nesse contexto, propÃe-se ainda uma soluÃÃo para o fator de ambiguidade multiplicativa do mÃtodo baseado em EVD, utilizando um simples produto de Khatri-Rao. Na segunda parte desta dissertaÃÃo, as propriedades dos sistemas VL-MIMO sÃo empregadas num problema de localizaÃÃo de fontes, a fim de determinar a direÃÃo de chegada (DOA) dos sinais incidentes sobre o arranjo, provenientes da cÃlula em questÃo. Explorando o subespaÃo de representaÃÃo dos sinais interferentes, propÃe-se o uso de um algoritmo de classificaÃÃo de tipo MUSIC para estimar a matriz de canal de forma cega. O mÃtodo proposto converte os altos ganhos de resoluÃÃo dos arranjos VL-MIMO em capacidade de reduÃÃo de interferÃncia, podendo fornecer estimativas do canal adequadas, mesmo sob nÃveis fortes de interferÃncia e tambÃm em casos onde os sinais do usuÃrio desejado e dos interferentes sÃo altamente correlacionados espacialmente. Extensas campanhas de simulaÃÃo computacional foram realizadas, dandoum carÃter exploratÃrio a esta dissertaÃÃo no sentido de abranger diferentes cenÃrios e avaliar as tÃcnicas investigadas em comparaÃÃo com soluÃÃes jà consolidadas, permitindo assim a elaboraÃÃo de um panorama mais completo de caracterizaÃÃo dos problemas de estimaÃÃo de parÃmetros no caso VL-MIMO. / The aim of this dissertation is mainly to investigate and propose different channel estimation techniques for a multicell multiuser multiple-input multiple-output (MIMO) communication system. Particular attention is payed to the case that is referred to as very large (VL) MIMO (VL-MIMO) arrays, where the base stations are equipped with a great (or even huge) number of antenna sensors. Some of these techniques exploit properties issued from the (large) Random Matrices Theory and are therefore less affected by the so-called pilot contamination effect. In this work, the parameters of the VL-MIMO channel are estimated from the eigenvalue decomposition (EVD) of the output covariance matrix of the receive antenna array. This technique is more robust to the interference of signals from other cells compared with methods that do not exploit the specific properties of the VL-MIMO channel matrix, which is the case of the classical least squares (LS) solution. In this context, this work also proposes a simpler way to resolve the scaling ambiguity remaining from the EVD-based method using the Khatri-Rao product. The second part of this dissertation exploits the VL-MIMO properties on a source localization problem, aiming to determine the direction of arrival (DoA) of the signals impinging on the antenna array from a given desired cell. Based on the subspace representation of the outer cell interference signals, we propose a new blind MUSIC-like classification algorithm to estimate the channel matrix. The proposed technique convert the high resolution gains of the VL-MIMO arrays into ability to reduce power of undesired signals, yielding good channel estimates even under high interference power levels, and including cases where desired and undesired signals are strongly correlated. Computer simulations have been done in order to cope with different situations and propagation scenarios, thus yielding an exploratory character to our research and allowing us to evaluate and assess the investigated algorithms, comparing them to consolidated solutions in order to establish a complete overview of the parameter estimation problem in the VL-MIMO case.