[pt] Neste trabalho é feito um estudo sobre compressão de imagens para canal ruidoso.Inicialmente, esquemas de complexidade moderada sem a utilização do princípio da separação de Shannon são investigados e simulados. Com isso, mostra-se que esquemas eficientes de codificação conjunta fonte/canal existem e podem eventualmente apresentar melhor performance do que esquemas separados de codificação e canal e fonte. São também investigados, algoritmos de codificação de imagens visando a transmissão num capital ruidoso. Nesse contexto, é proposto um esquema utilizando transformadas com superposição com boa performance, como mostram as simulações realizadas. O esquema posteriormente estendido para imagens multi- espectrais mostrando-se igualmente eficiente. / [en] In the present dissertation we investigate image compression techniques for transmission over binary symmetric channels poluted with noise. Frist we simulate some known techniques for joint source/channel coding that dispenses with the use of error correcting codes. These techiniques may exhibit better performance when complexity and delay constraits are at stake. We further propose an image compression algorithm for noisy channels based on lapped/block transforms and block source/channel coding. We simulate the proposed scheme for various channel situations. The algorithm is further extented to handle compression and transmission of multiepectral remote sensing satellite imagery. Results for natural and multiespectral images are presented showing the good performance attained by the proposed schemes.

In video transmission there is a need to compose a wide-band signal from a numberof narrow-band sub-signals. A flexible solution offers the possibility to place any narrow-band sub-signal anywhere in the wide-band signal, making better use of the frequency space of the wide-band signal. A multi-standard supportive solution will also consider the three standard bandwidths of digital and analog video transmissions, both terrestrial and cable (6; 7 and 8 MHz), in use today. This thesis work will study the efficiency of a flexible aggregation solution, in terms of computational complexity and error vector magnitude (EVM). The solution uses oversampled complex modulated filter banks and inner channelizers, to reduce the total workload on the system. Each sub-signal is channelized through an analysis filter bank and together all channelized sub-signals are aggregated through one synthesis filter bank to form the wide-band composite signal. The EVM between transmitted and received sub-signals are investigated for an increasing number of sub-signals. The solution in this thesis work is performing good for the tested number of up to 100 narrow-band sub-signals. The result indicates that the multi-standard flexible aggregation solution is efficient for an increasing number of transmitted sub-signals.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-12-21T11:00:37Z No. of bitstreams: 1 diegofagundesfabri.pdf: 7852736 bytes, checksum: 4ef1280e3a0eec15710a86fe8cad43ea (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-12-22T12:36:18Z (GMT) No. of bitstreams: 1 diegofagundesfabri.pdf: 7852736 bytes, checksum: 4ef1280e3a0eec15710a86fe8cad43ea (MD5) / Made available in DSpace on 2016-12-22T12:36:18Z (GMT). No. of bitstreams: 1 diegofagundesfabri.pdf: 7852736 bytes, checksum: 4ef1280e3a0eec15710a86fe8cad43ea (MD5) Previous issue date: 2011-03-03 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho, é realizada uma proposta de implementação de um analisador de harmônicos variantes no tempo para operação em tempo real, utilizando plataforma DSP TMS320F28027. O algoritmo utilizado para realização da decomposição harmônica é o da DFT de Janela Deslizante (Sliding-Window Recursive DFT). Este algoritmo é descrito completamente e são realizados estudos referentes à decomposição de sinais contendo inter-harmônicos ou variações na frequência fundamental, bem como são definidos parâmetros e uma estrutura para auxiliar na análise de presença de espalhamento espectral nas decomposições. Também é proposto um método para correção dos erros de amplitude e fase causados pelos filtros analógicos de entrada, a partir da manipulação dos componentes em quadratura da DFT. O algoritmo da DFT de Janela Deslizante é então implementado em plataforma DSP e são realizadas decomposições harmônicas de sinais reais através de um analisado protótipo proposto. Esta nova forma de análise no domínio do tempo dos harmônicos permite a observação e estudos de diversos fenômenos relacionados ao sistema de potência atual, de um novo ponto de vista. Além do estudo da DFT e do protótipo proposto, é realizado o desenvolvimento de uma nova estrutura de banco de filtros FIR QMF visando a decomposição harmônica. / This work proposes an implementation of a real-time time-varying harmonic analyzer using a DSP TMS320F28027 platform. The algorithm used to perform the harmonic decomposition is the Sliding-Window Recursive DFT. This algorithm is fully described, and studies are made concerning the decomposition of signals containing inter-harmonics and variations in their fundamental frequency. In addition to that, new parameters and an auxiliar structure are defined to assist the analysis of spillover presence in the signals decomposition. It is also proposed a method for correcting amplitude and phase errors caused by analog input filters, through the manipulation of the DFT quadrature components. The Sliding-Window DFT algorithm is then implemented in a DSP platform, and harmonic decompositions of real signals are performed using the proposed prototype. This new form of time-domain harmonics analysis allows the observation and study of various phenomena related to the power system from a new point of view. Besides the study of the DFT and the proposed prototype, a new filter bank structure using QMF FIR filter for harmonic decomposition is developed.

De nouveaux usages des systèmes de communications sans fils, tels que les réseaux de capteurs ou les voitures autonomes, ont émergé au cours des dernières années. Ces usages sont fondamentalement différents des applications haut-débit actuelles des réseaux cellulaires. La future technologie mobile, la 5G New Radio, introduit donc le concept de numérologie du signal afin de pouvoir satisfaire aux besoin hétérogènes des multiples applications supportées. En effet en supportant différentes numérologies de signaux, l'allocation temps/fréquence des signaux devient plus flexible et le signal transmis peut être adapté en conséquence. Cependant, supporte simultanément différentes numérologies génère de l'interférence et donc distord les signaux. Les filtrages spatiaux, comme la formation de faisceaux, est envisagée en 5G pour limiter l'interférence générée mais pour les communications au-dessus de 6 GHz. Il n'y a cependant pas de solutions proposées pour mes communications en-dessous de 6 GHz. Dans ce travail, des techniques d'atténuation des lobes secondaires sont étudiées pour faciliter le multiplexage des services pour les communications sous 6 GHz. L’interférence entre-utilisateurs est alors contrôlée mais la bande est également mieux utilisée. Une solution innovante, combinant bancs de filtres et orthogonalité complexe, est proposée. L'orthogonalité complexe est garanti grâce à un précodage OFDM qui remplace le précodage OQAM communément utilisé. De plus, le système développé, le Block-Filtered OFDM, utilise un récepteur 5G classique ce qui garantit la retro-compatibilité avec les techniques déjà déployée. Le modèle du BF-OFDM est entièrement décrit et adapté aux normes des réseaux mobiles. De plus, de multiples méthodes de conception des filtres prototypes sont proposées afin de mieux répondre aux besoins des systèmes. La forme d'onde étudiée est également comparée avec les autres solutions de l'état de l'art sur des scénarios d'étude classiques mais également adaptés aux nouveaux enjeux des technologies sans fils. / New use cases for wireless communications recently emerged ranging from massive sensor networks to connected cars. These applications highly differ from typical signals supported by already deployed mobile technologies, which are mainly high data rate pipes. The forthcoming generation of mobile technology, 5G New Radio, introduces the concept of signal numerology so as to properly serve the requirements of the diverse applications it will support. Indeed by considering different numerologies, the time/frequency signal allocation is made more flexible which allows to shape the transmitted signal according to its needs. However, multiplexing signals with different numerologies generates interference and therefore signal distortion. Spatial filtering, such as beamforming, is envisioned for 5G above 6-GHz communications to limit inter-user interference. However, this issue still holds for sub-6 GHz systems where spatial filtering is not considered in 5G.In this work, we consider side lobe rejection techniques to ease service multiplexing in sub-6 GHz bands. Not only it provides inter-user interference mitigation but it also improves the bandwidth use efficiency in bands where frequency is a scarce resource. A novel solution, mixing filter-bank for confined spectrum and complex orthogonality for a straightforward re-use of known-how 4G/5G techniques, is proposed. The complex orthogonality is restored thanks to an OFDM precoding substituting the commonly used Offset-QAM signaling which limits the orthogonality to the real field. Moreover, the proposed solution, named Block-Filtered Orthogonal Frequency Division Multiplexing (BFOFDM), relies on a simple 5G receiver scheme which makes it backward compatible with already deployed technologies.The BF-OFDM system model is fully described and adapted to cellular standards. Besides, different prototype filter designs methods are proposed to either improve the intrinsic interference attenuation or to better confined the spectrum of the transmitted signal. Last but not least, the proposed waveform will be compared with state-of-the-art solutions for both typical and 5G oriented evaluation scenarios such as multi-service coexistence.

Résumé: Les systèmes de substitution sensorielle convertissent des stimuli d’une modalité sensorielle en des stimuli d’une autre modalité. Ils peuvent fournir les moyens pour les personnes handicapées de percevoir des stimuli d’une modalité défectueuse par une autre modalité. Le but de ce projet de recherche était d’étudier des systèmes de substitution de l’audition vers la vision. Ce type de substitution n’est pas bien étudié probablement en raison de la complexité du système auditif et des difficultés résultant de la désadaptation entre les sons audibles qui peuvent changer avec des fréquences allant jusqu’à 20000 Hz et des stimuli visuels qui changent très lentement avec le temps afin d’être perçus. Deux problèmes spécifiques des systèmes de substitution de l’audition vers la vision ont été ciblés par cette étude: la recherche de correspondances audiovisuelles et l’extraction de caractéristiques auditives. Une expérience audiovisuelle a été réalisée en ligne pour trouver les associations entre les caractéristiques auditives (la fréquence fondamentale et le timbre) et visuelles (la forme, la couleur, et la position verticale). Une forte corrélation entre le timbre des sons utilisés et des formes visuelles a été observée. Les sujets ont fortement associé des timbres “doux” avec des formes arrondies bleues, vertes ou gris clair, des timbres “durs” avec des formes angulaires pointues rouges, jaunes ou gris foncé et des timbres comportant simultanément des éléments de douceur et de dureté avec un mélange des deux formes visuelles arrondies et angulaires. La fréquence fondamentale n’a pas été associée à la position verticale, ni le niveau de gris ou la couleur. Étant donné la correspondance entre le timbre et une forme visuelle, dans l’étape sui- vante, un modèle hiérarchique flexible et polyvalent bio-inspiré pour analyser le timbre et extraire des caractéristiques importantes du timbre a été développé. Inspiré par les découvertes dans les domaines des neurosciences, neurosciences computationnelles et de la psychoacoustique, non seulement le modèle extrait-il des caractéristiques spectrales et temporelles d’un signal, mais il analyse également les modulations d’amplitude sur différentes échelles de temps. Il utilise un banc de filtres cochléaires pour résoudre les composantes spectrales d’un son, l’inhibition latérale pour améliorer la résolution spectrale, et un autre banc de filtres de modulation pour extraire l’enveloppe temporelle et la rugosité du son à partir des modulations d’amplitude. Afin de démontrer son potentiel pour la représentation du timbre, le modèle a été évalué avec succès pour trois applications : 1) la comparaison avec les valeurs subjectives de la rugosité 2) la classification d’instruments de musique 3) la sélection de caractéristiques pour les sons qui ont été regroupés en fonction de la forme visuelle qui leur avait été attribuée dans l’expérience audiovisuelle. La correspondance entre le timbre et la forme visuelle qui a été révélée par cette étude et le modèle proposé pour l’analyse de timbre peuvent être utilisés pour développer des systèmes de substitution de l’audition vers la vision intuitifs codant le timbre en formes visuelles. / Abstract: Sensory substitution systems encode a stimulus modality into another stimulus modality. They can provide the means for handicapped people to perceive stimuli of an impaired modality through another modality. The purpose of this study was to investigate auditory to visual substitution systems. This type of sensory substitution is not well-studied probably because of the complexities of the auditory system and the difficulties arising from the mismatch between audible sounds that can change with frequencies up to 20000 Hz and visual stimuli that should change very slowly with time to be perceived. Two specific problems of auditory to visual substitution systems were targeted in this research: the investigation of audiovisual correspondences and the extraction of auditory features. An audiovisual experiment was conducted online to find the associations between the auditory (pitch and timbre) and visual (shape, color, height) features. One hundred and nineteen subjects took part in the experiments. A strong association between timbre of envelope normalized sounds and visual shapes was observed. Subjects strongly associated soft timbres with blue, green or light gray rounded shapes, harsh timbres with red, yellow or dark gray sharp angular shapes and timbres having elements of softness and harshness together with a mixture of the previous two shapes. Fundamental frequency was not associated with height, grayscale or color. Given the correspondence between timbre and shapes, in the next step, a flexible and multipurpose bio-inspired hierarchical model for analyzing timbre and extracting the important timbral features was developed. Inspired by findings in the fields of neuroscience, computational neuroscience, and psychoacoustics, not only does the model extract spectral and temporal characteristics of a signal, but it also analyzes amplitude modulations on different timescales. It uses a cochlear filter bank to resolve the spectral components of a sound, lateral inhibition to enhance spectral resolution, and a modulation filter bank to extract the global temporal envelope and roughness of the sound from amplitude modulations. To demonstrate its potential for timbre representation, the model was successfully evaluated in three applications: 1) comparison with subjective values of roughness, 2) musical instrument classification, and 3) feature selection for labeled timbres. The correspondence between timbre and shapes revealed by this study and the proposed model for timbre analysis can be used to develop intuitive auditory to visual substitution systems that encode timbre into visual shapes.

<p>Speech recognition is widely applied to translation from speech to related text, voice driven commands, human machine interface and so on [1]-[8]. It has been increasingly proliferated to Human’s lives in the modern age. To improve the accuracy of speech recognition, various algorithms such as artificial neural network, hidden Markov model and so on have been developed [1], [2].</p> <p>In this thesis work, the tasks of speech recognition with various classifiers are investigated. The classifiers employed include the support vector machine (SVM), k-nearest neighbors (KNN), random forest (RF) and convolutional neural network (CNN). Two novel features extraction methods of sparse discrete wavelet decomposition (SDWD) and bandpass filtering (BPF) based on the Mel filter banks [9] are developed and proposed. In order to meet diversity of classification algorithms, one-dimensional (1D) and two-dimensional (2D) features are required to be obtained. The 1D features are the array of power coefficients in frequency bands, which are dedicated for training SVM, KNN and RF classifiers while the 2D features are formed both in frequency domain and temporal variations. In fact, the 2D feature consists of the power values in decomposed bands versus consecutive speech frames. Most importantly, the 2D feature with geometric transformation are adopted to train CNN.</p> <p>Speech recognition including males and females are from the recorded data set as well as the standard data set. Firstly, the recordings with little noise and clear pronunciation are applied with the proposed feature extraction methods. After many trials and experiments using this dataset, a high recognition accuracy is achieved. Then, these feature extraction methods are further applied to the standard recordings having random characteristics with ambient noise and unclear pronunciation. Many experiment results validate the effectiveness of the proposed feature extraction techniques.</p>

Software radios (SWR) have been proposed for wireless communication systems to enable them to operate according to incompatible wireless communication standards by implementing most analog functions in the digital section on software-reprogrammable hardware. However, this significantly increases the required computations for SWR functionality, mainly because of the digital front-end computationally intensive filtering functions, such as sample rate conversion (SRC), channelization, and equalization. For increasing the computational efficiency of SWR systems, two new SRC methods with better performance than conventional SRC methods are presented. In the first SRC method, we modify the conventional CIC filters to enable them to perform SRC on slightly oversampled signals efficiently. We also describe a SRC method with high efficiency for SRC by factors greater than unity at which SRC in SWR systems may be computationally demanding. This SRC method efficiently increases the sample rate of wideband signals, especially in SWR base station transmitters, by applying Lagrange interpolation for evaluating output samples hierarchically using a low-rate signal that is computed with low cost from the input signal. A new channelizer/synthesizer is also developed for extracting/combining frequency multiplexed channels in SWR transceivers. The efficiency of this channelizer/synthesizer, which uses modulated perfect reconstruction (PR) filter banks, is higher than polyphase filter banks (when applicable) for processing few channels, and significantly higher than discrete filter banks for processing any number of variable-bandwidth channels where polyphase filter banks are inapplicable. Because the available methods for designing modulated PR filter banks are inapplicable due to the required number of subchannels and stopband attenuation of the prototype filters, a new design method for these filter banks is introduced. This method is reliable and significantly faster than the existing methods. Modulated PR filter banks are also considered for implementing a frequency-domain block blind equalizer capable of equalizing SWR signals transmitted though channels with long impulse responses and severe intersymbol interference (ISI). This blind equalizer adapts by using separate sets of weights to correct for the magnitude and phase distortion of the channel. The adaptation of this blind equalizer is significantly more reliable and its computational requirements increase at a lower rate compared to conventional time-domain equalizers making it efficient for equalizing long channels that exhibit severe ISI.

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)

Submitted by JULIO CEZAR UZINSKI null (uzinski.jc@gmail.com) on 2016-12-15T21:43:22Z No. of bitstreams: 1 Uzinski JC.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-12-20T16:20:21Z (GMT) No. of bitstreams: 1 uzinski_jc_dr_ilha.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) / Made available in DSpace on 2016-12-20T16:20:21Z (GMT). No. of bitstreams: 1 uzinski_jc_dr_ilha.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) Previous issue date: 2016-11-25 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. Para ilustrar o funcionamento e as vantagens da técnica proposta, alguns exemplos de decomposição de sinais no contexto de processamento de sinais mostrando que ela proporciona os mesmos coeficientes wavelet que a transformada wavelet rápida, e uma aplicação em controle através de realimentação dinâmica de estados também são apresentados nesta tese. / This thesis presents a state-space parameterization for the fast wavelet transform. This parameterization is based on orthonormal basis functions and finite impulse response filters at the same time, since the fast wavelet transform is an algorithm, which converts a signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite wavelet functions. Advantages presented by both proposals are incorporated. Finite impulse response systems have attractive properties, for instance, computational and analytical advantages, BIBO stability and robustness guarantee to some parameter changes, and others. On the other hand, orthonormal basis functions have some characteristics that make them attractive for dynamic systems modeling, examples are, output recursion absence, not requiring prior regression vector exact structure knowledge; possibility of increasing the model representation capacity by increasing the number of orthonormal functions employed; natural outputs uncoupling in multivariable models; tolerance to unmodeled dynamics, and others. Furthermore, the state-space realization is minimal. The contribution of this work consists in the development of a state-space realization for a wavelet filter bank, with the explicit presence of the parameters that can be freely adjusted, keeping perfect-reconstruction and orthonormality guarantees. In order to illustrate advantages and how the proposed technique works, some decomposition examples in signal processing context are presented showing that it provides the same wavelet coefficients as the fast wavelet transform, and an application on dynamic state feedback control is also presented in this thesis. / CNPq: 160545/2013-7

Orientador: Francisco Villarreal Alvarado / Resumo: Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. ... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor