Submitted by Patrícia Cerveira (pcerveira1@gmail.com) on 2017-06-06T18:58:56Z No. of bitstreams: 1 Felipe Frasson- Dissertação.pdf: 984658 bytes, checksum: 05ae4f112679292aefe890dc2f563010 (MD5) / Rejected by Biblioteca da Escola de Engenharia (bee@ndc.uff.br), reason: Patrícia, o formulário de submissão apresenta vários erros, informações duplicadas e fora da formatação (orientador, coorientador, resumo, dentre outros). Atenciosamente, Catarina Ribeiro Bibliotecária BEE - Ramal 5992 on 2017-06-29T16:53:14Z (GMT) / Submitted by Patrícia Cerveira (pcerveira1@gmail.com) on 2017-06-29T19:32:38Z No. of bitstreams: 1 Felipe Frasson- Dissertação.pdf: 984658 bytes, checksum: 05ae4f112679292aefe890dc2f563010 (MD5) / Approved for entry into archive by Biblioteca da Escola de Engenharia (bee@ndc.uff.br) on 2017-07-03T13:00:12Z (GMT) No. of bitstreams: 1 Felipe Frasson- Dissertação.pdf: 984658 bytes, checksum: 05ae4f112679292aefe890dc2f563010 (MD5) / Made available in DSpace on 2017-07-03T13:00:12Z (GMT). No. of bitstreams: 1 Felipe Frasson- Dissertação.pdf: 984658 bytes, checksum: 05ae4f112679292aefe890dc2f563010 (MD5) / Em um sistema de comunica c~oes, os sinais s~ao transmitidos atrav es de canais de comunica c~ao que, idealmente, deveriam transportar os dados de maneira a n~ao causar distor c~ao alguma. Por em, em sistemas reais, existem limita c~oes que interferem neste processo causando degrada c~ao nas informa c~oes transmitidas, podendo comprometer sua recep c~ao. Tais limita c~oes ocorrem devido a presen ca de ru do aditivo, e principalmente por interfer^encia intersimb olica, esta caracterizada pela sobreposi c~ao de s mbolos gerados por uma mesma fonte transmissora. A equaliza c~ao de canal e uma das t ecnicas existentes que reduzem os efeitos da interfer^encia intersimb olica, dando maior con abilidade e robustez aos sistemas de comunica c~oes. Dentre as t ecnicas utilizadas para equaliza c~ao de canal, o uso de algoritmo adaptativos vem sendo amplamente utilizados devido as suas propriedades de se auto-ajustarem as varia c~oes que ocorrem ao longo do tempo. Este trabalho tem como objetivo veri car o comportamento de diferentes tipos de algoritmos adaptativos cegos ou semicegos, assim denominados por n~ao utilizarem sequ^encias de treinamento, aplicados a equaliza c~ao de canais esparsos. Canais esparsos s~ao encontrados em diversos sistemas de comunica c~oes como, por exemplo, na comunica c~ao sem o (telefonia m ovel, transmiss~ao de r adio e TV), ou, ainda, em canais subaqu aticos. Os algoritmos foram escolhidos com base em recentes estudos desta aplica c~ao, que operam em modo cego ou semicego e utilizam estat sticas de alta ordem, como os algoritmos Bussgang e Matching Pursuit. Os algoritmos foram implementados em ambiente de simula c~ao computacional no qual foram utilizados canais esparsos simples e de resposta ao impulso conhecida, permitindo comparar o comportamento dos diferentes algoritmos, em termos do sinal recuperado, e da inversa da resposta ao impulso do canal original. / In communications systems, information signals are transmitted through communications channels that, ideally, are delivered without distortions. However, on real communications channels there are limitations that interferes on the process, reducing the probability to recover the original signal at receiver. These distortions are basically thermal noise and Intersymbol Interference (ISI), caused by superposition on the received symbols received from the same source. Channel Equalization acts reducing these distortions, bringing more reliability to communications systems. The objective of this work is to verify di erent adaptive algorithms behavior, applied to sparse channel equalization problem. Many communications systems have sparse channels, like broadcast radio, television, mobile telephony and underwater communications. The selected algorithms used in this work includes high order statistics algorithms family, like Bussgang and Matching Pursuit. This kind of algorithms are widely used, with high relevance, for blind channel equalization. The selected algorithms were submitted to computer simulations using simple sparse channels and knowledge about their impulse response, in order to analyze their behavior in therms of bit error rate and the inverse impulse response of the channel.

ABSTRACT The detection of an emergency signal can be estimated by the cancellation of surrounding noise and achieving the desired signal in order to alert the automobilist. The aim of the thesis is to detect the emergency signal arriving nearer to the automobilist carrying hearing aids. Recent studies show that this can be achieved by designing various kinds of fixed and adaptive beam formers. A beam former does spatial filtering in the sense that it separates two signals with overlapping frequency content originating from distinctive directions. In this contribution, robust beam former namely Wiener beam former is designed and analyzed collaboratively in a group under the consideration of hearing aid constraints such as the microphone distance. A fractionally delay (FD) are designed to get a maximally flat group delay. The studies had been carried out by comparing noise cancellation algorithms like LMS, NLMS, LLMS and RLS algorithms. By comparing Omni-directional and multi-directional microphones the SNR can be studied. In this thesis work, first proposing appropriate microphone array setup with improved beam forming techniques by using required adaptive algorithm (NLMS) in order to get better quality using the Microphone arrays. Microphone arrays have been widely used to improve the performance of speech recognition systems as well as to benefit for people who need hearing aids. With the help of microphone arrays, it can choose to focus on signals from a specific direction. To getting better signal quality in microphone array using adaptive algorithms, these are help in the noise suppression in accordance with the different beam forming techniques. The proposed system is implemented successfully and validated using MATLAB simulation tool. The emergency signal is different in different countries, so we identify any type of emergency signal by training through neural networks. / Vamshi Krishna Lakum: +46760190899

This thesis looks at hardware algorithms that help reduce dynamic power dissipation in video encoder applications. Computational complexity of motion estimation and the data traffic between external memory and the video processing engine are two main reasons for large power dissipation in video encoders. While motion estimation may consume 50% to 70% of total video encoder power, the power dissipated in external memory such as the DDR SDRAM can be of the order of 40% of the total system power. Reducing power dissipation in video encoders is important in order to improve battery life of mobile devices such as the smart phones and digital camcorders. We propose hardware algorithms which extract only the important features in the video data to reduce the complexity of computations, communications and storage, thereby reducing average power dissipation. We apply this concept to design hardware algorithms for optimizing motion estimation matching complexity, and reference frame storage and access from the external memory. In addition, we also develop techniques to reduce searching complexity of motion estimation. First, we explore a set of adaptive algorithms that reduce average power dissipated due to motion estimation. We propose that by taking into account the macro-block level features in the video data, the average matching complexity of motion estimation in terms of number of computations in real-time hardwired video encoders can be significantly reduced when compared against traditional hardwired implementations, that are designed to handle most demanding data sets. Current macro-block features such as pixel variance and Hadamard transform coefficients are analyzed, and are used to adapt the matching complexity. The macro-block is partitioned based on these features to obtain sub-block sums, which are used for matching operations. Thus, simple macro-blocks, without many features can be matched with much less computations compared to the macro-blocks with complex features, leading to reduction in average power dissipation. Apart from optimizing the matching operation, optimizing the search operation is a powerful way to reduce motion estimation complexity. We propose novel search optimization techniques including (1) a center-biased search order and (2) skipping unlikely search positions, both applied in the context of real time hardware implementation. The proposed search optimization techniques take into account and are compatible with the reference data access pattern from the memory as required by the hardware algorithm. We demonstrate that the matching and searching optimization techniques together achieve nearly 65% reduction in power dissipation due to motion estimation, without any significant degradation in motion estimation quality. A key to low power dissipation in video encoders is minimizing the data traffic between the external memory devices such as DDR SDRAM and the video processor. External memory power can be as high as 50% of the total power budget in a multimedia system. Other than the power dissipation in external memory, the amount of data traffic is an important parameter that has significant impact on the system cost. Large memory traffic necessitates high speed external memories, high speed on-chip interconnect, and more parallel I/Os to increase the memory throughput. This leads to higher system cost. We explore a lossy, scalar quantization based reference frame compression technique that can be used to reduce the amount of reference data traffic from external memory devices significantly. In this scheme, the quantization is adapted based on the pixel range within each block being compressed. We show that the error introduced by the scalar quantization is bounded and can be represented by smaller number of bits compared to the original pixel. The proposed reference frame compression scheme uses this property to minimize the motion compensation related traffic, thereby improving the compression scheme efficiency. The scheme maintains a fixed compression ratio, and the size of the quantization error is also kept constant. This enables easy storage and retrieval of reference data. The impact of using lossy reference on the motion estimation quality is negligible. As a result of reduction in DDR traffic, the DDR power is reduced significantly. The power dissipation due to additional hardware required for reference frame compression is very small compared to the reduction in DDR power. 24% reduction in peak DDR bandwidth and 23% net reduction in average DDR power is achieved. For video sequences with larger motion, the amount of bandwidth reduction is even higher (close to 40%) and reduction in power is close to 30%.

This thesis deals with the development of a new adaptive algorithm for three-dimensional fluid flows based on a residual error estimator. The residual, known as the R –parameter has been successfully extended to three dimensions using a novel approach for arbitrary grid topologies. The computation of the residual error estimator in three dimensions is based on a least-squares based reconstruction and the order of accuracy of the latter is critical in obtaining a consistent estimate of the error. The R –parameter can become inconsistent on three–dimensional meshes depending on the grid quality. A Zero Mean Polynomial(ZMP) which is k–exact, and which preserves the mean has been used in this thesis to overcome the problem. It is demonstrated that the ZMP approach leads to a more accurate estimation of solution derivatives as opposed to the conventional polynomial based least-squares method. The ZMP approach is employed to compute the R –parameter which is the n used to derive the criteria for refinement and derefinement. Studies on three different complex test problems involving inviscid, laminar and turbulent flows demonstrate that the new adaptive algorithm is capable of detecting the sources of error efficiently and lead to accurate results independent of the grid topology.

[EN] Common audio systems are designed with the intent of creating real and immersive scenarios that allow the user to experience a particular acoustic sensation that does not depend on the room he is perceiving the sound. However, acoustic devices and multichannel rendering systems working inside a room, can impair the global audio effect and thus the 3D spatial sound. In order to preserve the spatial sound characteristics of multichannel rendering techniques, adaptive filtering schemes are presented in this dissertation to compensate these electroacoustic effects and to achieve the immersive sensation of the desired acoustic system. Adaptive filtering offers a solution to the room equalization problem that is doubly interesting. First of all, it iteratively solves the room inversion problem, which can become computationally complex to obtain when direct methods are used. Secondly, the use of adaptive filters allows to follow the time-varying room conditions. In this regard, adaptive equalization (AE) filters try to cancel the echoes due to the room effects. In this work, we consider this problem and propose effective and robust linear schemes to solve this equalization problem by using adaptive filters. To do this, different adaptive filtering schemes are introduced in the AE context. These filtering schemes are based on three strategies previously introduced in the literature: the convex combination of filters, the biasing of the filter weights and the block-based filtering. More specifically, and motivated by the sparse nature of the acoustic impulse response and its corresponding optimal inverse filter, we introduce different adaptive equalization algorithms. In addition, since audio immersive systems usually require the use of multiple transducers, the multichannel adaptive equalization problem should be also taken into account when new single-channel approaches are presented, in the sense that they can be straightforwardly extended to the multichannel case. On the other hand, when dealing with audio devices, consideration must be given to the nonlinearities of the system in order to properly equalize the electroacoustic system. For that purpose, we propose a novel nonlinear filtered-x approach to compensate both room reverberation and nonlinear distortion with memory caused by the amplifier and loudspeaker devices. Finally, it is important to validate the algorithms proposed in a real-time implementation. Thus, some initial research results demonstrate that an adaptive equalizer can be used to compensate room distortions. / [ES] Los sistemas de audio actuales están diseñados con la idea de crear escenarios reales e inmersivos que permitan al usuario experimentar determinadas sensaciones acústicas que no dependan de la sala o situación donde se esté percibiendo el sonido. Sin embargo, los dispositivos acústicos y los sistemas multicanal funcionando dentro de salas, pueden perjudicar el efecto global sonoro y de esta forma, el sonido espacial 3D. Para poder preservar las características espaciales sonoras de los sistemas de reproducción multicanal, en esta tesis se presentan los esquemas de filtrado adaptativo para compensar dichos efectos electroacústicos y conseguir la sensación inmersiva del sistema sonoro deseado. El filtrado adaptativo ofrece una solución al problema de salas que es interesante por dos motivos. Por un lado, resuelve de forma iterativa el problema de inversión de salas, que puede llegar a ser computacionalmente costoso para los métodos de inversión directos existentes. Por otro lado, el uso de filtros adaptativos permite seguir las variaciones cambiantes de los efectos de la sala de escucha. A este respecto, los filtros de ecualización adaptativa (AE) intentan cancelar los ecos introducidos por la sala de escucha. En esta tesis se considera este problema y se proponen esquemas lineales efectivos y robustos para resolver el problema de ecualización mediante filtros adaptativos. Para conseguirlo, se introducen diferentes esquemas de filtrado adaptativo para AE. Estos esquemas de filtrado se basan en tres estrategias ya usadas en la literatura: la combinación convexa de filtros, el sesgado de los coeficientes del filtro y el filtrado basado en bloques. Más especificamente y motivado por la naturaleza dispersiva de las respuestas al impulso acústicas y de sus correspondientes filtros inversos óptimos, se presentan diversos algoritmos adaptativos de ecualización específicos. Además, ya que los sistemas de audio inmersivos requieren usar normalmente múltiples trasductores, se debe considerar también el problema de ecualización multicanal adaptativa cuando se diseñan nuevas estrategias de filtrado adaptativo para sistemas monocanal, ya que éstas deben ser fácilmente extrapolables al caso multicanal. Por otro lado, cuando se utilizan dispositivos acústicos, se debe considerar la existencia de no linearidades en el sistema elactroacústico, para poder ecualizarlo correctamente. Por este motivo, se propone un nuevo modelo no lineal de filtrado-x que compense a la vez la reverberación introducida por la sala y la distorsión no lineal con memoria provocada por el amplificador y el altavoz. Por último, es importante validar los algoritmos propuestos mediante implementaciones en tiempo real, para asegurarnos que pueden realizarse. Para ello, se presentan algunos resultados experimentales iniciales que muestran la idoneidad de la ecualización adaptativa en problemas de compensación de salas. / [CAT] Els sistemes d'àudio actuals es dissenyen amb l'objectiu de crear ambients reals i immersius que permeten a l'usuari experimentar una sensació acústica particular que no depèn de la sala on està percebent el so. No obstant això, els dispositius acústics i els sistemes de renderització multicanal treballant dins d'una sala poden arribar a modificar l'efecte global de l'àudio i per tant, l'efecte 3D del so a l'espai. Amb l'objectiu de conservar les característiques espacials del so obtingut amb tècniques de renderització multicanal, aquesta tesi doctoral presenta esquemes de filtrat adaptatiu per a compensar aquests efectes electroacústics i aconseguir una sensació immersiva del sistema acústic desitjat. El filtrat adaptatiu presenta una solució al problema d'equalització de sales que es interessant baix dos punts de vista. Per una banda, el filtrat adaptatiu resol de forma iterativa el problema inversió de sales, que pot arribar a ser molt complexe computacionalment quan s'utilitzen mètodes directes. Per altra banda, l'ús de filtres adaptatius permet fer un seguiment de les condicions canviants de la sala amb el temps. Més concretament, els filtres d'equalització adaptatius (EA) intenten cancel·lar els ecos produïts per la sala. A aquesta tesi, considerem aquest problema i proposem esquemes lineals efectius i robustos per a resoldre aquest problema d'equalització mitjançant filtres adaptatius. Per aconseguir-ho, diferent esquemes de filtrat adaptatiu es presenten dins del context del problema d'EA. Aquests esquemes de filtrat es basen en tres estratègies ja presentades a l'estat de l'art: la combinació convexa de filtres, el sesgat dels pesos del filtre i el filtrat basat en blocs. Més concretament, i motivat per la naturalesa dispersa de la resposta a l'impuls acústica i el corresponent filtre òptim invers, presentem diferents algorismes d'equalització adaptativa. A més a més, com que els sistemes d'àudio immersiu normalment requereixen l'ús de múltiples transductors, cal considerar també el problema d'equalització adaptativa multicanal quan es presenten noves solucions de canal simple, ja que aquestes s'han de poder estendre fàcilment al cas multicanal. Un altre aspecte a considerar quan es treballa amb dispositius d'àudio és el de les no linealitats del sistema a l'hora d'equalitzar correctament el sistema electroacústic. Amb aquest objectiu, a aquesta tesi es proposa una nova tècnica basada en filtrat-x no lineal, per a compensar tant la reverberació de la sala com la distorsió no lineal amb memòria introduïda per l'amplificador i els altaveus. Per últim, és important validar la implementació en temps real dels algorismes proposats. Amb aquest objectiu, alguns resultats inicials demostren la idoneïtat de l'equalització adaptativa en problemes de compensació de sales. / Fuster Criado, L. (2015). Linear and nonlinear room compensation of audio rendering systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59459 / TESIS

Cette thèse est consacrée à la restauration et l'estimation des paramètres par filtrage dans les modèles de chaîne de Markov cachée classique, couple et triplet à sauts Markoviens. Nous proposons deux nouvelles méthodes d'approximation dans le cas des systèmes linéaires gaussiens à sauts Markoviens. La première est fondée sur l'utilisation des chaînes de Markov cachées par du bruit à mémoire longue, on obtient alors une méthode " partiellement non supervisée" dans la quelle certains paramètres, peuvent être estimés en utilisant une version adaptative de l'algorithme EM ou ICE, les résultats obtenus sont encourageant et comparables avec les méthodes classiquement utilisées du type (Kalman/Particulaire). La deuxième exploite l'idée de ne garder à chaque instant que les trajectoires les plus probables; là aussi, on obtient une méthode très rapide donnant des résultats très intéressants. Nous proposons par la suite deux familles de modèles à sauts qui sont originaux. la première est très générale où le processus couple composé du processus d'intérêt et celui des observations conditionnellement aux sauts, est une chaîne de Markov cachée, et nous proposons une extension du filtrage particulaire à cette famille. La deuxième, est une sous famille de la première où le couple composé de la chaîne des sauts et le processus d'observations est Markovien dans ce dernier cas le filtrage optimal exact est possible avec une complexité linéaire dans le temps. L'utilisation de la deuxième famille en tant qu'approximation de la première est alors étudiée et les résultats exposés dans ce mémoire semblent très encourageants / This thesis is devoted to the restoration problem and the parameter estimation by filtering in the traditional hidden Markov chain model, couple and triplet with Markovian jumps. We propose two new approximate methods in the case of Gaussian linear systems with Markovian jumps. first is founded to use the hidden Markov chains by noise with long memory, we obtains a method " partially not supervised" some parameters, can be estimated by using an adaptive version of EM or ICE algorithm, the results obtained are encouraging and comparable with the methods used classically (Kalman/Particle). The second one exploits idea to keep at every moment only the most probable trajectories; we obtains a very fast method giving very interesting results. Then we propose two families of models to jumps which are original. The first one is very general where the process couples made up of the hidden and the observations process conditionally to the jumps, are a hidden Markov chain, and we propose an extension of particulate filtering to this family. The second is under family of the first, where the couple made up of the jumps and the observations process is Markovian, in this last case exact optimal filtering is possible with a linear complexity in time. Using of the second family to approach the first one is studied and the results exposed in this memory seem very encouraging

O objetivo da desconvolução cega de imagens é restaurar uma imagem degradada sem usar informação da imagem real ou da função de degradação. O mapeamento dos níveis de cinza de uma imagem em um sinal de comunicação possibilita o uso de técnicas de equalização cega de canais para a restauração de imagens. Neste trabalho, propõe-se o uso de um esquema para desconvolução cega de imagens baseado na combinação convexa de um equalizador cego com um equalizador no modo de decisão direta. A combinação também é adaptada de forma cega, o que possibilita o chaveamento automático entre os filtros componentes. Dessa forma, o esquema proposto é capaz de atingir o desempenho de um algoritmo de filtragem adaptativa supervisionada sem o conhecimento prévio da imagem original. O desempenho da combinação é ilustrado por meio de simulações, que comprovam a eficiência desse esquema quando comparado a outras soluções da literatura. / The goal of blind image deconvolution is to restore a degraded image without using information from the actual image or from the point spread function. The mapping of the gray levels of an image into a communication signal enables the use of blind equalization techniques for image restoration. In this work, we use a blind image deconvolution scheme based on the convex combination of a blind equalizer with an equalizer in the decision-directed mode. The combination is also blindly adapted, which enables automatic switching between the component filters. Thus, the proposed scheme is able to achieve the performance of a supervised adaptive filtering algorithm without prior knowledge of the original image. The performance of the combination is illustrated by simulations, which show the efficiency of this scheme when compared to other solutions in the literature.

O objetivo da desconvolução cega de imagens é restaurar uma imagem degradada sem usar informação da imagem real ou da função de degradação. O mapeamento dos níveis de cinza de uma imagem em um sinal de comunicação possibilita o uso de técnicas de equalização cega de canais para a restauração de imagens. Neste trabalho, propõe-se o uso de um esquema para desconvolução cega de imagens baseado na combinação convexa de um equalizador cego com um equalizador no modo de decisão direta. A combinação também é adaptada de forma cega, o que possibilita o chaveamento automático entre os filtros componentes. Dessa forma, o esquema proposto é capaz de atingir o desempenho de um algoritmo de filtragem adaptativa supervisionada sem o conhecimento prévio da imagem original. O desempenho da combinação é ilustrado por meio de simulações, que comprovam a eficiência desse esquema quando comparado a outras soluções da literatura. / The goal of blind image deconvolution is to restore a degraded image without using information from the actual image or from the point spread function. The mapping of the gray levels of an image into a communication signal enables the use of blind equalization techniques for image restoration. In this work, we use a blind image deconvolution scheme based on the convex combination of a blind equalizer with an equalizer in the decision-directed mode. The combination is also blindly adapted, which enables automatic switching between the component filters. Thus, the proposed scheme is able to achieve the performance of a supervised adaptive filtering algorithm without prior knowledge of the original image. The performance of the combination is illustrated by simulations, which show the efficiency of this scheme when compared to other solutions in the literature.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-06-23T20:42:44Z No. of bitstreams: 1 CesarCasteloBranco.pdf: 11257769 bytes, checksum: 911c33f2f0ba5c1c0948888e713724f6 (MD5) / Made available in DSpace on 2017-06-23T20:42:44Z (GMT). No. of bitstreams: 1 CesarCasteloBranco.pdf: 11257769 bytes, checksum: 911c33f2f0ba5c1c0948888e713724f6 (MD5) Previous issue date: 2016-12-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ) / This work proposes new methodologies to optimize the choice of the parameters of the proportionate normalized least-mean-square (PNLMS) adaptive algorithms. The proposed approaches use procedures based on two optimization methods, namely, the golden section and tabu search methods. Such procedures are applied to determine the optimal parameters in each iteration of the adaptation process of the PNLMS and improved PNLMS (IPNLMS) algorithms. The objective function for the proposed procedures is based on the a posteriori estimation error. Performance studies carried out to evaluate the impact of the PNLMS and IPNLMS parameters in the behavior of these algorithms shows that, with the aid of optimization techniques to choose properly such parameters, the performance of these algorithms may be improved in terms of convergence speed for the identification of plants with high sparseness degree. The main goal of the proposed methodologies is to improve the distribution of the adaptation energy between the coefficients of the PNLMS and IPNLMS algorithms, using parameter values that lead to the minimal estimation error of each iteration of the adaptation process. Numerical tests performed (considering various scenarios in which the plant impulse response is sparse) show that the proposed methodologies achieve convergence speeds faster than the PNLMS and IPNLMS algorithms, and other algorithms of the PNLMS class, such as the sparseness controlled IPNLMS (SC-IPNLMS) algorithm. / Neste trabalho, novas metodologias para otimizar a escolha dos parâmetros dos algoritmos adaptativos LMS normalizados proporcionais (PNLMS) são propostas. As abordagens propostas usam procedimentos baseados em dois métodos de otimização, a saber, os métodos da razão áurea e da busca tabu. Tais procedimentos são empregados para determinar os parâmetros ótimos em cada iteração do processo de adaptação dos algoritmos PNLMS e PNLMS melhorado (IPNLMS). A função objetivo adotada pelos procedimentos propostos é baseada no erro de estimação a posteriori. O estudo de desempenho realizado para avaliar o impacto dos parâmetros dos algoritmos PNLMS e IPNLMS no comportamento dos mesmos mostram que, com o auxílio de técnicas de otimização para escolher adequadamente tais parâmetros, o desempenho destes algoritmos pode ser melhorado, em termos de velocidade de convergência, para a identificação de plantas com elevado grau de esparsidade. O principal objetivo das metodologias propostas é melhorar a distribuição da energia de ativação entre os coeficientes dos algoritmos PNLMS e IPNLMS, usando valores de parâmetros que levam ao erro de estimação mínimo em cada iteração do processo de adaptação. Testes numéricos realizados (considerando diversos cenários nos quais a resposta impulsiva da planta é esparsa) mostram que as metodologias propostas alcançam velocidades de convergência superiores às dos algoritmos PNLMS e IPNLMS, além de outros algoritmos da classe PNLMS, tais como o algoritmo IPNLMS com controle de esparsidade (SCIPNLMS).

The goal of this term project is create user friendly client of Twitter. They may use methods of machine learning as naive bayes classifier to mentions new interests tweets. For visualissation this tweets will be use hyperbolic trees and some others methods.