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Στην παρούσα διπλωματική αναπτύχθηκε μια μέθοδος ψηφιακής επεξεργασίας σημάτων για ακουστικά σήματα συμβατή με πραγματικού χρόνου επεξεργασία. Αρχικά έγινε περίληψη των λειτουργιών των επεξεργαστών ειδικού σκοπου. Έγινε μελέτη της ανάλυσης στο πεδίο της συχνότητας καθώς και της συνάρτησης συνεκτικότητας. Για τους σκοπούς της διπλωματικής υλοποιήθηκε αλγόριθμος αφαίρεσης θορύβου από σήματα ομιλίας που αξιοποιεί την συνάρτηση συνεκτικότητας και χρησιμοποιεί είσοδο από δύο μικρόφωνα. Ο αλγόριθμος αυτός υλοποιήθηκε και δοκιμάστικε σε μη-πραγματικό χρόνο σε μαθηματικό λογισμικό , καθώς και σε πραγματικό χρόνο σε επεξεργαστή ειδικού σκοπού. / In this thesis, a method of digital signal processing for acoustic signals was developed, compatible with real-time processing. At first, a review of the operations that special purpose digital signal processors feature. We also studied the frequency domain analysis and the coherence function in depth. For the purposes of this thesis an algorithm of noise reduction from speech signals was implemented, that exploits the coherence function and takes two microphone signals as inputs. The algorithm was implemented offline in a mathematical software, as well as real time in a special purpose digital signal processor.

In modern digital audio applications, a continuous audio signal stream is sampled at a fixed sampling rate, which is always greater than twice the highest frequency of the input signal, to prevent aliasing. A more energy efficient approach is to dynamically change the sampling rate based on the input signal. In the dynamic sampling rate technique, fewer samples are processed when there is little frequency content in the samples. The perceived quality of the signal is unchanged in this technique. Processing fewer samples involves less computation work; therefore processor speed and voltage can be reduced. This reduction in processor speed and voltage has been shown to reduce power consumption by up to 40% less than if the audio stream had been run at a fixed sampling rate.

The Generalized Sidelobe Canceller is an adaptive algorithm for optimally estimating the parameters for beamforming, the signal processing technique of combining data from an array of sensors to improve SNR at a point in space. This work focuses on the algorithm’s application to widely-separated microphone arrays with irregular distributions used for human voice capture. Methods are presented for improving the performance of the algorithm’s blocking matrix, a stage that creates a noise reference for elimination, by proposing a stochastic model for amplitude correction and enhanced use of cross correlation for phase correction and time-difference of arrival estimation via a correlation coefficient threshold. This correlation technique is also applied to a multilateration algorithm for an efficient method of explicit target tracking. In addition, the underlying microphone array geometry is studied with parameters and guidelines for evaluation proposed. Finally, an analysis of the stability of the system is performed with respect to its adaptation parameters.

Separating unknown signal mixtures into their constituent parts is a difficult problem in signal processing called blind source separation. One of the benchmark problems in this area is the extraction of the fetal heartbeat from an electrocardiogram in which it is overshadowed by a strong maternal heartbeat. This thesis presents a study of a signal separation technique called independent component analysis (ICA), in order to assess its suitability for the maternal-fetal ECG separation problem. This includes an analysis of ICA on deterministic, stochastic, simulated and recorded ECG signals. The experiments presented in this thesis demonstrate that ICA is effective on linear mixtures of known simulated or recorded ECGs. The performance of ICA was measured using visual comparison, heart rate extraction, and energy, information theoretic, and fractal-based measures. ICA extraction of clinically recorded maternal-fetal ECGs mixtures, in which the source signals were unknown, were successful at recovering the fetal heart rate.

Music can positively affect game play and help players to understand underlying patterns in the game, or the effects of their actions on the characters. Conversely, inappropriate music can have a negative effect on players. While game makers recognize the effects of music on game play, solutions that provide users with a choice in personal music have not been forthcoming. I designed and evaluated an algorithm for automatically adapting any music track from a personal library so that is plays at the same rate as the user plays the game. I accomplish this without access to the video game's souce code, allowing deployment with any game and no modifications to the system.

Στα πλαίσια αυτής της διπλωματικής εργασίας υλοποιήθηκε η σύσταση G.721 της International Telecommunication Union (ITU-CCITT) η οποία περιγράφει την προσαρμοστική διαφορική παλμοκωδική διαμόρφωση (Adaptive Differential Pulse Code Modulation-ADPCM) για κανάλια 32 Kbps με συχνότητα δειγματοληψίας 8 KHz. Η διαμόρφωση αυτή χρησιμοποιείται για συμπίεση δεδομένων σε πραγματικό χρόνο, ιδίως φωνής, κατά τη μετάδοση σε ένα τηλεπικοινωνιακό κανάλι. Πρόκειται για μια από τις παλαιότερες τεχνικές κωδικοποίησης φωνής, η οποία εκμεταλλεύεται την υψηλή συσχέτιση των φωνητικών σημάτων παρέχοντας υψηλή απόδοση. Η υλοποίηση πραγματοποιήθηκε στην αναπτυξιακή κάρτα C6211/C6711 DSK, πυρήνας της οποίας είναι ο ψηφιακός επεξεργαστής σήματος κινητής υποδιαστολής TMS320C6711 της Texas Instruments. Ένα από τα βασικά χαρακτηριστικά της οικογένειας TMS320 στην οποία αυτός ανήκει είναι η προχωρημένη Very Long Instruction Word (VLIW) αρχιτεκτονική, VelociTITM, η οποία παρέχει υψηλό παραλληλισμό πολλών βαθμίδων για την εκτέλεση πολλών εντολών στη διάρκεια ενός ωρολογιακού κύκλου. Η υψηλή απόδοση αυτού του επεξεργαστή, η ύπαρξη μετατροπέων A/D και D/A που εξασφαλίζουν την εύκολη είσοδο και έξοδο πραγματικών σημάτων, η ύπαρξη ενός πλήρους συνόλου αναπτυξιακών εργαλείων λογισμικού για εύκολο προγραμματισμό (Code Composer Studio v.1.23) κι η εύκολη διασύνδεση της αναπτυξιακής κάρτας με προσωπικό υπολογιστή, μέσω της παράλληλης θύρας επικοινωνιών, την καθιστούν ένα ισχυρό εργαλείο για την ανάπτυξη εφαρμογών της ψηφιακής επεξεργασίας σημάτων, της επεξεργασίας και συμπίεσης φωνής, τηλεπικοινωνιακών εφαρμογών κ.ά. Η εργασία αυτή δομείται σε τρία κεφάλαια. Στο 1ο κεφάλαιο περιγράφονται τα βασικά χαρακτηριστικά του επεξεργαστή TMS320C6711, στο 2ο κεφάλαιο, η σύσταση G.721 και στο 3ο περιγράφεται η υλοποίηση του αλγορίθμου μαζί με τις πειραματικές μετρήσεις και τα συμπεράσματα. Τέλος, στο παράρτημα, παρατίθενται όλοι οι χρησιμοποιούμενοι κώδικες που αφορούν τον αλγόριθμο και την αναπαράσταση των αποτελεσμάτων. / Recommendation G.721 of the International Telecommunication Union (ITU-CCITT) that describes Adaptive Differential Pulse Code Modulation (ADPCM) for 32 Kbps channels with 8 KHz sampling frequency has been implemented within the framework of this diploma thesis. This modulation is utilized for real-time data compression, especially voice data, during transmission in telecommunications channels. It is one of the oldest well-known voice coding techniques that exploits high correlation inherit in speech signals and provides high performance. The implementation of ADPCM voice coding has been carried out in the C6211/C6711 Digital signal processing Starter Kit (DSK), which core processor is the floating point Digital Signal Processor (DSP) TMS320C6711 of Texas Instruments. This processor belongs to the TMS320 DSP family which one of the main characteristics is the advanced Very Long Instruction Word (VLIW) architecture, VelociTITM. The latter architecture provides high multistage parallelism for executing many commands during a clocking cycle. DSK’s easy connection with personal computers through the parallel communications port, DSP’s TMS320C6711 high performance, the existence of A/D and D/A converters that ensure simple input and output of real signals and the supporting of solid software development tools for easy programming (Code Composer Studio v.1.23) render DSK a powerful tool for implementing digital signal processing applications, speech processing and compression, telecommunications applications etc. This thesis is structured in three chapters. In Chapter 1, the basic characteristics of DSP TMS320C6711 are presented, whereas in Chapter 2, recommendation G.721 is described. The implementation of ADPCM source coding is presented in Chapter 3 along with several simulation results and conclusions. In the appendix, all source files are included.

Este trabalho trata de conceitos relacionados à qualidade da Energia Elétrica (EE) e, neste contexto, apresenta a proposta de técnicas para a compressão da representação de transitórios rápidos e da análise tempo-frequência de distúrbios elétricos em geral. A qualidade da Energia Elétrica é medida pelo coeficiente de desvios que os sinais de tensão e corrente apresentam em relação ao sinal senoidal ideal. Tais desvios são denominados de distúrbios, podendo ser classificados como quase estacionários (e.g. distorção de harmônicas) e eventos (e.g. transitórios rápidos). No contexto de EE, os transitórios rápidos possuem pequena duração (i.e. na ordem dos microssegundos), são detectados por altas taxas de amostragem (i.e. na ordem dos MHz) e possuem difícil parametrização. Portanto, as representações das formas de onda geralmente são armazenadas para auxiliar a avaliação subjetiva dos transitórios e dos parâmetros de interesse. Consequentemente, a compressão destas formas de onda torna-se de extrema importância para armazenar dados adquiridos por longos períodos de tempo, e estes modos de compressão são tratados nesta dissertação. Em virtude das altas taxas de amostragem utilizadas, uma técnica baseada em Análise de Componentes Principais (PCA – Principal Component Analysis) é proposta para esta representação mais compacta de transitórios. Resultados mostram que o desempenho em compressão versus qualidade de reconstrução é semelhante ao de trabalhos relacionados com a vantagem de atender aos requisitos de altas taxas de amostragem. A análise tempo-frequência é um mecanismo que auxilia na classificação e caracterização dos distúrbios elétricos. Neste trabalho, a Transformada de Hilbert-Huang é estudada e uma proposta de melhoria na Decomposição Empírica de Modos (EMD – Empirical Mode Decomposition) é apresentada. Nossos resultados mostram que a técnica proposta economiza o custo computacional se comparada com o estado da arte. Em virtude disso, a técnica proposta apresenta uma taxa de redução no tempo médio de execução de 99,76 % em relação à técnica do estado da arte. Além disso, uma verificação acerca do desempenho em eficiência de compressão versus qualidade de reconstrução de trabalhos anteriores é também desenvolvida nesta dissertação. Foi utilizada uma sistemática de avaliação experimental com base em amostras de sinais AC, de forma a avaliar as taxas de compressão atingidas pelas técnicas estudadas, como a Transformada Wavelet Discreta. Resultados mostram que a Transformada Wavelet falha para compressão de todo e qualquer tipo de distúrbio elétrico quando analisado o compromisso entre acuidade de reconstrução versus eficiência de compressão. / This work deals with concepts related to the AC Power Quality theoretical framework and, in this scope, proposes techniques for the representation of fast transient data compression and for the power line disturbances time-frequency analysis. The AC power quality is measured by the differences between actual and ideal sinusoidal voltage/current signals. These differences are known as electrical disturbances, which can be classified as quasi-stationary (e.g. harmonic distortion) or events (e.g. surge or fast transients) disturbances. In the AC Power Quality scope, the fast transients have short duration (i.e. typically on the order of microseconds), are detected by high sampling rates (i.e. typically on the order of MHz), and are hard to characterize and parameterize. Hence, the resultant representation of the waveforms is in general stored to help in the subjective evaluation of these fast transients and their parameters of interest. As a consequence the compression turns out to be of main concern, in order to store this information acquired over long periods of time (like weeks or months). In this work, a compression technique is proposed taking into account the high sampling rates. The proposed technique makes use of the Principal Component Analysis (PCA) for such compact representation of fast transients. The Compression efficiency versus reconstruction accuracy results show a similar performance for the proposed technique when compared to the related works. On the other hand, the proposed technique can handle the large amount of data provided by the high sampling rates. The time-frequency analysis helps in the classification and characterization of AC power quality disturbances. In this work, the Hilbert-Huang Transform is studied and a modification is proposed in order to improve the Empirical Mode Decomposition (EMD) performance. Our results show that the proposed modification can save computational cost when compared to the state-of-the-art. Therefore, the average execution time is reduced to 99.76 % in comparison with the state-of-the-art technique. Besides that, this work also revisits previous techniques based on the Discrete Wavelet Transform (DWT) in order to verify the trade-off between reconstruction accuracy versus compression efficiency under a more systematic experimental evaluation setup, considering samples of real AC signals. Results show that DWT fails as a general-purpose technique in AC Power Quality scope.

Multi-dimensional digital signals have become an intertwined part of day to day life, from digital images and videos used to capture and share life experiences, to more powerful scene representations such as light field images, which open the gate to previously challenging tasks, such as post capture refocusing or eliminating visible occlusions from a scene. This dissertation delves into the world of multi-dimensional signal processing and introduces a tool of particular use for gradient based solutions of well-known signal processing problems. Specifically, a technique to reconstruct a signal from a given gradient data set is developed in the case of two dimensional (2-D), three dimensional (3-D) and four dimensional (4-D) digital signals. The reconstruction technique is multiresolution in nature, and begins by using the given gradient to generate a multi-dimensional Haar wavelet decomposition of the signals of interest, and then reconstructs the signal by Haar wavelet synthesis, performed on successive resolution levels. The challenges in developing this technique are non-trivial and are brought about by the applications at hand. For example, in video content replacement, the gradient data from which a video sequence needs to be reconstructed is a combination of gradient values that belong to different video sequences. In most cases, such operations disrupt the conservative nature of the gradient data set. The effects of the non-conservative nature of the newly generated gradient data set are attenuated by using an iterative Poisson solver at each resolution level during the reconstruction. A second and more important challenge is brought about by the increase in signal dimensionality. In a previous approach, an intermediate extended signal with symmetric region of support is obtained, and the signal of interest is extracted from it. This approach is reasonable in 2-D, but becomes less appealing as the signal dimensionality increases. To avoid generating data that is then discarded, a new approach is proposed, in which signal extension is no longer performed. Instead, different procedures are suggested to generate a non-symmetric Haar wavelet decomposition of the signals of interest. In the case of 2-D and 3-D signals, ways to obtain this decomposition exactly from the given gradient data and the average value of the signal are proposed. In addition, ways to approximate a subset of decomposition coefficients are introduced and the visual consequences of such approximations are studied in the special case of 2-D digital images. Several ways to approximate the same subset of decomposition coefficients are developed in the special case of 4-D light field images. Experiments run on various 2-D, 3-D and 4-D test signals are included to provide an insight on the performance of the reconstruction technique. The value of the multi-dimensional reconstruction technique is then demonstrated by including it in a number of signal processing applications. First, an efficient algorithm is developed with the purpose of combining information from the gradient of a set of 2-D images with different regions in focus or different exposure times, with the purpose of generating an all-in-focus image or revealing details that were lost due to improper exposure setting. Moving on to 3-D signal processing applications, two video editing problems are studied and gradient based solutions are presented. In the first one, the objective is to seamlessly place content from one video sequence in another, while in the second one, to combine elements from two video sequences and generate a transparency effect. Lastly, a gradient based technique for editing 4-D scene representations (light fields) is presented, as well as a technique to combine information from two light fields with the purpose of generating a light field with more details of the imaged scene. All these applications show that the developed technique is a reliable tool for gradient domain based solutions of signal processing problems. / Graduate