This thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations. Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method. The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.

In system identification scenario, the linear approximation of the system modelled by its impulse response, is estimated in real time by gradient type Least Mean Square (LMS) or Recursive Least Squares (RLS) algorithms. In recent applications like acoustic echo cancellation, the order of the impulse response to be estimated is very high, and these traditional approaches are inefficient and real time implementation becomes difficult. Alternatively, the system is modelled by a set of shorter adaptive filters operating in parallel on subsampled signals. This approach, referred to as subband adaptive filtering, is expected to reduce not only the computational complexity but also to improve the convergence rate of the adaptive algorithm. But in practice, different subband adaptive algorithms have to be used to enhance the performance with respect to complexity, convergence rate and processing delay. A single subband adaptive filtering algorithm which outperforms the full band scheme in all applications is yet to be realized. This thesis is intended to study the subband adaptive filtering techniques and explore the possibilities of better algorithms for performance improvement. Three different subband adaptive algorithms have been proposed and their performance have been verified through simulations. These algorithms have been applied to acoustic echo cancellation and EEG artefact minimization problems. Details of the work To start with, the fast FIR filtering scheme introduced by Mou and Duhamel has been generalized. The Perfect Reconstruction Filter Bank (PRFB) is used to model the linear FIR system. The structure offers efficient implementation with reduced arithmetic complexity. By using a PRFB with non adjacent filters non overlapping, many channel filters can be eliminated from the structure. This helps in reducing the complexity of the structure further, but introduces approximation in the model. The modelling error depends on the stop band attenuation of the filters of the PRFB. The error introduced due to approximation is tolerable for applications like acoustic echo cancellation. The filtered output of the modified generalized fast filtering structure is given by (formula) where, Pk(z) is the main channel output, Pk,, k+1 (z) is the output of auxiliary channel filters at the reduced rate, Gk (z) is the kth synthesis filter and M the number of channels in the PRFB. An adaptation scheme is developed for adapting the main channel filters. Auxiliary channel filters are derived from main channel filters. Secondly, the aliasing problem of the classical structure is reduced without using the cross filters. Aliasing components in the estimated signal results in very poor steady state performance in the classical structure. Attempts to eliminate the aliasing have reduced the computation gain margin and the convergence rate. Any attempt to estimate the subband reference signals from the aliased subband input signals results in aliasing. The analysis filter Hk(z) having the following antialiasing property (formula) can avoid aliasing in the input subband signal. The asymmetry of the frequency response prevents the use of real analysis filters. In the investigation presented in this thesis, complex analysis filters and real'synthesis filters are used in the classical structure, to reduce the aliasing errors and to achieve superior convergence rate. PRFB is traditionally used in implementing Interpolated FIR (IFIR) structure. These filters may not be ideal for processing an input signal for an adaptive algorithm. As third contribution, the IFIR structure is modified using discrete finite frames. The model of an FIR filter s is given by Fc, with c = Hs. The columns of the matrix F forms a frame with rows of H as its dual frame. The matrix elements can be arbitrary except that the transformation should be implementable as a filter bank. This freedom is used to optimize the filter bank, with the knowledge of the input statistics, for initial convergence rate enhancement . Next, the proposed subband adaptive algorithms are applied to acoustic echo cancellation problem with realistic parameters. Speech input and sufficiently long Room Impulse Response (RIR) are used in the simulations. The Echo Return Loss Enhancement (ERLE)and the steady state error spectrum are used as performance measures to compare these algorithms with the full band scheme and other representative subband implementations. Finally, Subband adaptive algorithm is used in minimization of EOG (Electrooculogram) artefacts from measured EEG (Electroencephalogram) signal. An IIR filterbank providing sufficient isolation between the frequency bands is used in the modified IFIR structure and this structure has been employed in the artefact minimization scheme. The estimation error in the high frequency range has been reduced and the output signal to noise ratio has been increased by a couple of dB over that of the fullband scheme. Conclusions Efforts to find elegant Subband adaptive filtering algorithms will continue in the future. However, in this thesis, the generalized filtering algorithm could offer gain in filtering complexity of the order of M/2 and reduced misadjustment . The complex classical scheme offered improved convergence rate, reduced misadjustment and computational gains of the order of M/4 . The modifications of the IFIR structure using discrete finite frames made it possible to eliminate the processing delay and enhance the convergence rate. Typical performance of the complex classical case for speech input in a realistic scenario (8 channel case), offers ERLE of more than 45dB. The subband approach to EOG artefact minimization in EEG signal was found to be superior to their fullband counterpart. (Refer PDF file for Formulas)

<p>This thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations. </p><p>Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method. </p><p>The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.</p>

Η χρήση επαναληπτικών τεχνικών προσαρμοστικής ισοστάθμισης διαύλου αποτελεί μια σχετικά πρόσφατη και πολλά υποσχόμενη μέθοδο αντιμετώπισης του φαινομένου της διασυμβολικής παρεμβολής που εισάγεται από το κανάλι λόγω του φαινομένου της πολυδιόδευσης. Ο αλγόριθμος που έχει επικρατήσει στις περισσότερες προσαρμοστικές εφαρμογές είναι ο ελαχίστων μέσων τετραγώνων (LMS). Διακρίνεται για την απλότητά του, έχει όμως φτωχές ιδιότητες σύγκλισης. Η μέθοδος των αναδρομικών ελαχίστων τετραγώνων (RLS) είναι επίσης αρκετά διαδεδομένη και κατέχει υπερέχουσες ιδιότητες σύγκλισης. Ωστόσο παρουσιάζει μεγάλη υπολογιστική πολυπλοκότητα και αυξημένες απαιτήσεις σε μνήμη. Στα πλαίσια της εργασίας αυτής εγίνε μια προσπάθεια ανάλυσης των τεχνικών που βασίζονται στη μέθοδο των συζυγών παραγώγων (Conjugate Gradient), χρησιμοποιούνται σε προβλήματα προσαρμοστικού φιλτραρίσματος και πιο ειδικά στο πρόβλημα της προσαρμοστικής ισοστάθμισης διαύλου. Οι τεχνικές αυτές επεξεργάζονται τα δεδομένα και ανά μπλοκ. Είναι ικανές να παρέχουν ιδιότητες σύγκλισης συγκρίσιμες με αυτές της (RLS) μεθόδου, εισάγοντας υπολογιστική πολυπλοκότητα ενδιάμεσων απαιτήσεων μεταξύ των μεθόδων LMS και RLS χωρίς να παρουσιάζουν προβλήματα αριθμητικής ευστάθειας. / The use of iteration methods for adaptive equalization has received considerable attention during the past several decades. The Least Mean Squares (LMS) method, which has found widespread use owing to its simplicity, has poor convergence properties. The Recursive Least Squares (RLS) method possess superior convergence properties, but it is computationally intensive and has high storage requirements for matrix manipulations. In this MSc thesis the technique of conjugate gradients is applied for the adaptive filtering problem. Conjugate gradient algorithms for adaptive filtering applications suitable for efficient implementation has been developed and has been applied for the design of an adaptive transversal equalizer. Low cost block algorithms using the preconditioned conjugate gradient method are also discussed. The algorithms are capable of providing convergence comparable to RLS schemes at a computational complexity between the LMS and the RLS methods and does not suffer from any known instability problems.

This thesis discusses the use of Kalman filtering for noise reduction in a 3-D gesture- based computer music controller known as the Radio Drum and for real-time tempo tracking of rhythmic and melodic musical performances. The Radio Drum noise reduction Kalman filter is designed based on previous research in the field of target tracking for radar applications and prior knowledge of a drummer’s expected gestures throughout a performance. In this case we are seeking to improve the position estimates of a drum stick in order to enhance the expressivity and control of the instrument by the performer. Our approach to tempo tracking is novel in that a multi- modal approach combining gesture sensors and audio in a late fusion stage lead to higher accuracy in the tempo estimates.

Orientadora: Profa. Dra. Aline de Oliveira Neves Panazio / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, Santo André, 2018. / Este trabalho dedica-se ao estudo de algoritmos de filtragem adaptativa autodidata no modo difusão, com aplicações em redes de sensores sem fio (RSSF). No modo difusão, os nós sensores da rede possuem poder de processamento local e trocam informações com seus vizinhos. Neste trabalho, propomos dois algoritmos utilizando como base o algoritmo CMA no modo Difusão (CMAD), com duas abordagens distintas da técnica Set-Membership. O primeiro baseia-se no algoritmo Set-Membership Least Mean Squares (SM-LMS), desenvolvido também no modo difusão. Estendemos o algoritmo para o contexto não supervisionado, denotando por Algoritmo Set-Membership CMA no modo Difusão (SM-CMAD). Mostramos que este algoritmo apresenta desempenho melhor ou similar ao CMAD, em termos de velocidade de convergência, patamar de interferência intersimbólica (IIS) e possuindo a importante vantagem de reduzir as trocas de informações entre os nós, economizando energia e recursos da rede. O segundo algoritmo proposto se baseia no Set-Membership do Módulo Constante (SM-CM), o qual estendemos para o contexto de redes de sensores sem fio no modo difusão. Tal algoritmo é denotado por Algoritmo Set-membership CMA no modo Difusão Square-root Gamma (SM-CMAD-SG). Novamente o algoritmo apresenta um bom desempenho quando comparado com o CMAD e, quando comparado ao SM-CMAD, vemos que sua principal vantagem está na economia em termos de atualizações dos coeficientes do filtro, que chega a valores acima de 70% em diversos cenários de simulação, sem grandes perdas de desempenho economizando energia. / This work is devoted to the study of unsupervised adaptive filtering algorithms in diffusion mode, with applications in wireless sensor networks (WSNs). In diffusion mode, network sensing nodes have local processing power and exchange information with their neighbors. In this work, we propose two algorithms based on the CMA algorithm in Diffusion mode (CMAD), with two different approaches to the Set-Membership technique. The first one is based on the Set-Membership Least Mean Squares (SM-LMS) algorithm, also developed in the diffusion mode. We extend the algorithm to the unsupervised context, denoting by Set-Membership CMA in Diffusion mode (SM-CMAD). We show that this algorithm presents better or similar performance to CMAD, in terms of convergence speed, intersymbol interference threshold (IIS), and has the important advantage of reducing the exchange of information between nodes, saving energy and network resources. The second proposed algorithm is based on the Set-Membership of the Constant Modulus (SM-CM), which we extend to the context of wireless sensor networks in the diffusion mode. This algorithm is denoted by the Set-membership CMA in Diffusion mode Square-root Gamma (SM-CMAD-SG). This algorithm performs well when compared to CMAD and, when compared to SM-CMAD, we see that its main advantage lies in the economy in terms of the update of the filter coefficients, which reaches values above 70% in several scenarios without loss of performance, saving energy.

Made available in DSpace on 2016-08-17T14:52:41Z (GMT). No. of bitstreams: 1 Dissertacao-WilanderTestonePereiraSilva.pdf: 3903191 bytes, checksum: b91ff906a27937df64d75b330c6ea137 (MD5) Previous issue date: 2016-03-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this dissertation we present a research in aspects of stochastic modeling, convergence and applications of least mean square (LMS) algorithm, normalized least mean square (NLMS) algorithm and proportionate normalized least mean square (PNLMS) algorithm. Specifically, the aim is to address the LMS algorithm in your extension, defining his concepts, demonstrations of properties, algorithms and analysis of convergence, Learning Curve and Misadjustment of the algorithm in question. Within of the context of sensor networks and spatial filtering is evaluated the performance of the algorithms by the learning curve of the referred algorithms for arrangements of adaptive antennas. In the intrinsic context of the application in electrical engineering, in area of telecommunications that seek the best alternative and aims to optimize the process of transmission/reception to eliminate interference, and the least amount of elements in adaptive antenna arrays, which they are known as smart antenna, which aims to reach a signal noise ratio for small value, with appropriate number of elements. The performance of the LMS algorithm is evaluated in sensor networks that is characterized by an antenna array. Results of computer simulations for different scenarios of operation show that the algorithms have good numerical results of convergence to a suitable choice of the parameters related with the rate of learning that are associated with their average curves and the beamforming of the smart antenna array. / Nesta dissertação de mestrado apresenta-se uma investigação em aspectos de modelagem estocástica, convergência e aplicações dos algoritmos de mínimos quadrados médio (LMS), mínimos quadrados médio normalizado (NLMS) e mínimos quadrados médio normalizado proporcional (PNLMS). Particularmente, aborda-se o Algoritmo LMS em sua extensão, definindo conceitos, demonstrações de propriedades, algoritmos e análise de convergência, Curva de Aprendizagem e Desajuste do referido algoritmo. Dentro do contexto de redes de sensores e filtragem espacial avalia-se o desempenho dos algoritmos por meio da curva de aprendizagem dos referidos algoritmos para os arranjos de antenas adaptativas. No contexto intrínseco da aplicação em engenharia elétrica, isto é, na área de telecomunicações procura-se a melhor alternativa e almeja-se a otimização do processo de transmissão/recepção para eliminar interferências e a menor quantidade de elementos em arranjos de antenas adaptativas, que são conhecidas como antenas inteligentes, e que tem como objetivo atingir uma relação Sinal Ruído para valor pequeno, com número adequado de elementos. O desempenho do algoritmo LMS é avaliado em redes de sensores que é caracterizada por um arranjo de antenas. Resultados de simulações computacionais para diferentes cenários de operação mostram que os algoritmos apresentam bons resultados numéricos de convergência para uma escolha adequada dos parâmetros relacionados com a taxa de aprendizagem que são associadas com suas curvas médias e com a conformação de feixes do arranjo em antenas inteligentes.

Made available in DSpace on 2016-08-17T14:52:59Z (GMT). No. of bitstreams: 1 Jose Igor Santos de Oliveira.pdf: 3257339 bytes, checksum: 08e579c1308bf514ca6256e089894a3b (MD5) Previous issue date: 2005-09-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The level measurement, besides the applications in reservoirs of industrial processes, as in the industries chemical, pharmaceutical, chemical petroleum, of I refine of alumina etc, it is applicable also in reservoirs exposed outdoors, such as dikes, lakes and ponds, dams and other. To measure level in most of the cases has great impact in the people's safety, of the environment, and of the involved process, besides influencing in the quality of the final product. Level in several ways can be measured that space from a simple float to a sophisticated system for time of flight of waves that processes the information that returns after the emission of a sign. System as that can use several types of waves to take the information of the transmission, the most common are microwaves, infrared and the ultrasonic ones. In that work a method is described that is used of the technique of the time of flight with the use of ultrasonic waves in association with the adaptive filtering to determine the location of the levels of the liquids contained in a container of known height. It is made a study of robustness of the method with base in simulations, through the variation of the relationship sign noise and of the sampling tax, in comparison with the results obtained with the use of Hilbert Transform, Fourier Transform and Wavelet Transform, considering the time of processing and the measurement uncertainty. / A medição de nível, além das aplicações em reservatórios de processos industriais, como nas indústrias químicas, farmacêuticas, petroquímicas, de refino de alumina etc., é aplicável também em reservatórios expostos ao ar livre, tais como diques, lagos e lagoas, barragens e outros. Medir nível na maioria dos casos tem grande impacto na segurança das pessoas, do meio ambiente, e do processo envolvido, além de influenciar na qualidade do produto final. Pode-se medir nível de diversas formas que vão desde um simples flutuador até um sofisticado sistema por Tempo de Vôo de ondas que processa a informação que retorna na forma de eco refletido após a emissão de um sinal. Um Sistema como esse pode utilizar diversos tipos de ondas para levar a informação da transmissão, as mais comuns são microondas, infravermelhas e as ultra-sônicas. Nesse trabalho descreve-se um método que se utiliza da técnica do Tempo de Vôo com o uso de ondas ultra-sônicas em associação com a filtragem adaptativa para determinar a localização dos níveis dos líquidos contidos em um recipiente de altura conhecida. É feito um estudo de robustez do método com base em simulações, através da variação da relação sinal ruído e da taxa de amostragem. Compara-se com os resultados obtidos com o uso da Transformada de Hilbert, Transformada de Fourier e da Transformada Wavelets, considerando o tempo de processamento e a incerteza na medição.

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Táto práca sa zaoberá odstraňovaním šumu, ktorý vzniká z tzv. multilateračných meraní leteckých cieľov. Na tento účel bude využitá najmä teória Bayesovských odhadov. Odvodí sa aposteriórna hustota skutočnej (presnej) polohy lietadla. Spolu s polohou (alebo aj rýchlosťou) lietadla bude odhadovaná tiež geometria trajektórie lietadla, ktorú lietadlo v aktuálnom čase sleduje a tzv. procesný šum, ktorý charakterizuje ako moc sa skutočná trajektória môže od tejto líšiť. Odhad spomínaného procesného šumu je najdôležitejšou časťou tejto práce. Je odvodený prístup maximálnej vierohodnosti a Bayesovský prístup a ďalšie rôzne vylepšenia a úpravy týchto prístupov. Tie zlepšujú odhad pri napr. zmene manévru cieľa alebo riešia problém počiatočnej nepresnosti odhadu maximálnej vierohodnosti. Na záver je ukázaná možnosť kombinácie prístupov, t.j. odhad spolu aj geometrie aj procesného šumu.