The Synchronized Short-Time-Fourier-Transform: Properties and Definitions for Multichannel Source Separation.

This paper proposes the use of a synchronized linear transform, the synchronized short-time-Fourier-transform (sSTFT), for time-frequency analysis of anechoic mixtures. We address the short comings of the commonly used time-frequency linear transform in multichannel settings, namely the classical short-time-Fourier-transform (cSTFT). We propose a series of desirable properties for the linear transform used in a multichannel source separation scenario: stationary invertibility, relative delay, relative attenuation, and finally delay invariant relative windowed-disjoint orthogonality (DIRWDO). Multisensor source separation techniques which operate in the time-frequency domain, have an inherent error unless consideration is given to the multichannel properties proposed in this paper. The sSTFT preserves these relationships for multichannel data. The crucial innovation of the sSTFT is to locally synchronize the analysis to the observations as opposed to a global clock. Improvement in separation performance can be achieved because assumed properties of the time-frequency transform are satisfied when it is appropriately synchronized. Numerical experiments show the sSTFT improves instantaneous subsample relative parameter estimation in low noise conditions and achieves good synthesis

Automatic simultaneous measurement of phase velocity and thickness in composite plates using iterative deconvolution

A new method for the automatic and simultaneous measurement of phase velocity and thickness for thin composite plates was developed based on Ping He's method, without any need of a priori knowledge of the material parameters. Two composites were analyzed: a block of clean epoxy and a thin specimen of glass-fiber reinforced plastic produced by resin transfer molding. The proposed method combines cross-correlation functions and iterative deconvolution for accurate measurement of times of flight and gating. The new method has demonstrated to be more accurate than conventional Ping He's method, and can be implemented automatically thus saving processing time and increasing accuracy.This research was funded by a Project IN-SMART, Grant no. VP1-3.1SMM-10-V-02-012 and by the Spanish Ministerio de Ciencia e Innovacion (TEC2011-23403).Rodriguez Martinez, A.; Svilainis, L.; Dumbrava, V.; Chaziachmetovas, A.; Salazar Afanador, A. (2014). Automatic simultaneous measurement of phase velocity and thickness in composite plates using iterative deconvolution. NDT and E International. 66:117-127. https://doi.org/10.1016/j.ndteint.2014.06.001S1171276

Techniques to Improve the Efficiency of Data Transmission in Cable Networks

The cable television (CATV) networks, since their introduction in the late 1940s, have now become a crucial part of the broadcasting industry. To keep up with growing demands from the subscribers, cable networks nowadays not only provide television programs but also deliver two-way interactive services such as telephone, high-speed Internet and social TV features. A new standard for CATV networks is released every five to six years to satisfy the growing demands from the mass market. From this perspective, this thesis is concerned with three main aspects for the continuing development of cable networks: (i) efficient implementations of backward-compatibility functions from the old standard, (ii) addressing and providing solutions for technically-challenging issues in the current standard and, (iii) looking for prospective features that can be implemented in the future standard. Since 1997, five different versions of the digital CATV standard had been released in North America. A new standard often contains major improvements over the previous one. The latest version of the standard, namely DOCSIS 3.1 (released in late 2013), is packed with state-of-the-art technologies and allows approximately ten times the amount of traffic as compared to the previous standard, DOCSIS 3.0 (released in 2008). Backward-compatibility is a must-have function for cable networks. In particular, to facilitate the system migration from older standards to a newer one, the backward compatible functions in the old standards must remain in the newer-standard products. More importantly, to keep the implementation cost low, the inherited backward compatible functions must be redesigned by taking advantage of the latest technology and algorithms. To improve the backward-compatibility functions, the first contribution of the thesis focuses on redesigning the pulse shaping filter by exploiting infinite impulse response (IIR) filter structures as an alternative to the conventional finite impulse response (FIR) structures. Comprehensive comparisons show that more economical filters with better performance can be obtained by the proposed design algorithm, which considers a hybrid parameterization of the filter's transfer function in combination with a constraint on the pole radius to be less than 1. The second contribution of the thesis is a new fractional timing estimation algorithm based on peak detection by log-domain interpolation. When compared with the commonly-used timing detection method, which is based on parabolic interpolation, the proposed algorithm yields more accurate estimation with a comparable implementation cost. The third contribution of the thesis is a technique to estimate the multipath channel for DOCSIS 3.1 cable networks. DOCSIS 3.1 is markedly different from prior generations of CATV networks in that OFDM/OFDMA is employed to create a spectrally-efficient signal. In order to effectively demodulate such a signal, it is necessary to employ a demodulation circuit which involves estimation and tracking of the multipath channel. The estimation and tracking must be highly accurate because extremely dense constellations such as 4096-QAM and possibly 16384-QAM can be used in DOCSIS 3.1. The conventional OFDM channel estimators available in the literature either do not perform satisfactorily or are not suitable for the DOCSIS 3.1 channel. The novel channel estimation technique proposed in this thesis iteratively searches for parameters of the channel paths. The proposed technique not only substantially enhances the channel estimation accuracy, but also can, at no cost, accurately identify the delay of each echo in the system. The echo delay information is valuable for proactive maintenance of the network. The fourth contribution of this thesis is a novel scheme that allows OFDM transmission without the use of a cyclic prefix (CP). The structure of OFDM in the current DOCSIS 3.1 does not achieve the maximum throughput if the channel has multipath components. The multipath channel causes inter-symbol-interference (ISI), which is commonly mitigated by employing CP. The CP acts as a guard interval that, while successfully protecting the signal from ISI, reduces the transmission throughput. The problem becomes more severe for downstream direction, where the throughput of the entire system is determined by the user with the worst channel. To solve the problem, this thesis proposes major alterations to the current DOCSIS 3.1 OFDM/OFDMA structure. The alterations involve using a pair of Nyquist filters at the transceivers and an efficient time-domain equalizer (TEQ) at the receiver to reduce ISI down to a negligible level without the need of CP. Simulation results demonstrate that, by incorporating the proposed alterations to the DOCSIS 3.1 down-link channel, the system can achieve the maximum throughput over a wide range of multipath channel conditions

Frequency-domain bandwidth extension for low-delay audio coding applications

MPEG-4 Spectral Band Replication (SBR) is a sophisticated high-frequency reconstruction (HFR) tool for speech and natural audio which when used in conjunction with an audio codec delivers a broadband high-quality signal at a bit rate of 48 kbps or even below. The major drawback of this technique is that it significantly increases the delay of the underlying core codec. The idea of synthetic signal reconstruction is of particular interest also in real-time communications. There, a HFR method can be employed to further loosen the channel capacity requirements. In this thesis a delay-optimized derivative of SBR is elaborated, which can be used together with a low-delay speech and audio coder like the Fraunhofer ULD. The presented approach is based on a short-time subband representation of an acoustic signal of natural or artificial origin, and as such it utilizes a filter bank for the extraction and the manipulation of sound characteristics. The system delay for a combination of the ULD coder with the proposed low-delay bandwidth extension (LD-BWE) tool adds up to 12 ms at a sampling rate of 48 kHz. At the present stage, LD-BWE generates a subjectively confirmed excellent-quality highband replica at a simulated mean data rate of 12.8 kbps.MPEG-4 Spectral Band Replication (SBR) ist ein technisch ausgereiftes Verfahren zur Rückgewinnung von hochfrequenten Signalkomponenten für Sprache und natürliches Audio, das in Verbindung mit einem Audiocodec angewandt ein hochwertiges Breitbandsignal bei einer Bitrate von nicht mehr als 48 kbps liefert. Ein wesentlicher Nachteil dieser Methode ist, dass sie die Zeitverzögerung des darunter liegenden Kerncodecs maßgeblich vergrößert. Die Idee der synthetischen Signalwiederherstellung ist in Echtzeitkommunikation ebenso von besonderem Interesse. Ein derartiges Verfahren könnte dort eingesetzt werden, um die Anforderungen an die Kanalkapazität weiter zu lockern. In dieser Arbeit wird ein latenzoptimiertes Derivat von SBR ausgearbeitet, welches zusammen mit einem minimal verzögernden Sprach- und Audiocoder, wie dem Fraunhofer ULD, verwendet werden kann. Der vorgestellte Ansatz basiert auf einer Kurzzeit-Teilband-Darstellung eines akustischen Signals natürlichen oder künstlichen Ursprungs, und greift als solcher auf eine Filterbank zur Extraktion und Manipulation von Klangcharakteristika zurück. Die Verzögerungszeit des Gesamtsystems bestehend aus dem ULD-Coder und der vorgeschlagenen Bandbreitenerweiterung beläuft sich bei einer Abtastrate von 48 kHz auf 12 ms. Einem subjektiven Hörtest zufolge, erzeugt die neu entwickelte Bandbreitenerweiterung in ihrem derzeitigen Stadium eine Kopie des Hochbandes von hervorragender Qualität bei einer simulierten mittleren Datenrate von 12.8 kbps.Ilmenau, Techn. Univ., Masterarbeit, 201

Model-based Filtering of Interfering Signals in Ultrasonic Time Delay Estimations

This work presents model-based algorithmic approaches for interference-invariant time delay estimation, which are specifically suited for the estimation of small time delay differences with a necessary resolution well below the sampling time. Therefore, the methods can be applied particularly well for transit-time ultrasonic flow measurements, since the problem of interfering signals is especially prominent in this application

Model-based Filtering of Interfering Signals in Ultrasonic Time Delay Estimations

In dieser Arbeit werden modellbasierte algorithmische Ansätze zur Interferenz-invarianten Zeitverschiebungsschätzung vorgestellt, die speziell für die Schätzung kleiner Zeitverschiebungsdifferenzen mit einer notwendigen Auflösung, die deutlich unterhalb der Abtastzeit liegt, geeignet sind. Daher lassen sich die Verfahren besonders gut auf die Laufzeit-basierte Ultraschalldurchflussmessung anwenden, da hier das Problem der Interferenzsignale besonders ausgeprägt ist. Das Hauptaugenmerk liegt auf der Frage, wie mehrere Messungen mit unterschiedlichen Zeitverschiebungen oder Prozessparametern zur Unterdrückung der Interferenzsignale in Ultraschalldurchflussmessungen verwendet werden können, wobei eine gute Robustheit gegenüber additivem weißen Gauß\u27schen Rauschen und eine hohe Auflösung erhalten bleiben sollen. Zu diesem Zweck wird ein Signalmodell angenommen, welches aus stationären Interferenzsignalen, die nicht von wechselnden Zeitverschiebungen abhängig sind, und aus Zielsignalen, die den Messeffekt enthalten, besteht. Zunächst wird das Signalmodell einer Ultraschalldurchflussmessung und sein dynamisches Verhalten bei Temperatur- oder Zeitverschiebungsschwankungen untersucht. Ziel ist es, valide Simulationsdatensätze zu erzeugen, mit denen die entwickelten Methoden sowohl unter der Prämisse, dass die Daten perfekt zum Signalmodell passen, als auch unter der Prämisse, dass Modellfehler vorliegen, getestet werden können. Dabei werden die Eigenschaften der Signalmodellkomponenten, wie Bandbreite, Stationarität und Temperaturabhängigkeit, identifiziert. Zu diesem Zweck wird eine neue Methode zur Modellierung der Temperaturabhängigkeit der Interferenzsignale vorgestellt. Nach der Charakterisierung des gesamten Messsystems wird das Signalmodell -- angepasst an die Ultraschalldurchflussmessung -- als Grundlage für zwei neue Methoden verwendet, deren Ziel es ist, die Auswirkungen der Interferenzsignale zu reduzieren. Die erste vorgeschlagene Technik erweitert die auf der Signaldynamik basierenden Ansätze in der Literatur, indem sie die Voraussetzungen für die erforderliche Varianz der Zeitverschiebungen abschwächt. Zu diesem Zweck wird eine neue Darstellung von mehreren Messsignalen als Punktwolken eingeführt. Die Punktwolken werden dann mithilfe der Hauptkomponentenanalyse und B-Splines verarbeitet, was entweder zu Interferenz-invarianten Zeitverschiebungsschätzungen oder geschätzten Interferenzsignalen führt. In diesem Zusammenhang wird eine neuartige gemeinsame B-Spline- und Registrierungsschätzung entwickelt, um die Robustheit zu erhöhen. Der zweite Ansatz besteht in einer regressionsbasierten Schätzung der Zeitverschiebungsdifferenzen durch das Erlernen angepasster Signalunterräume. Diese Unterräume werden effizient durch die Analytische Wavelet Packet Transformation berechnet, bevor die resultierenden Koeffizienten in Merkmale transformiert werden, die gut mit den Zeitverschiebungssdifferenzen korrelieren. Darüber hinaus wird ein neuartiger, unbeaufsichtigter Unterraum-Trainingsansatz vorgeschlagen und mit den konventionellen Filter- und Wrapper-basierten Merkmalsauswahlmethoden verglichen. Schließlich werden beide Methoden in einem experimentellen Ultraschalldurchflussmesssystem mit einem hohen Maß an vorhandenen Interferenzsignalen getestet, wobei sich zeigt, dass sie in den meisten Fällen den Methoden aus der Literatur überlegen sind. Die Qualität der Methoden wird anhand der Genauigkeit der Zeitverschiebungsschätzung bewertet, da die Grundwahrheit für die Interferenzsignale nicht zuverlässig bestimmt werden kann. Anhand verschiedener Datensätze werden die Abhängigkeiten von den Hyperparametern, den Prozessbedingungen und, im Falle der regressionsbasierten Methode, dem Trainingsdatensatz analysiert

Localization in urban environments. A hybrid interval-probabilistic method

Ensuring safety has become a paramount concern with the increasing autonomy of vehicles and the advent of autonomous driving. One of the most fundamental tasks of increased autonomy is localization, which is essential for safe operation. To quantify safety requirements, the concept of integrity has been introduced in aviation, based on the ability of the system to provide timely and correct alerts when the safe operation of the systems can no longer be guaranteed. Therefore, it is necessary to assess the localization's uncertainty to determine the system's operability. In the literature, probability and set-membership theory are two predominant approaches that provide mathematical tools to assess uncertainty. Probabilistic approaches often provide accurate point-valued results but tend to underestimate the uncertainty. Set-membership approaches reliably estimate the uncertainty but can be overly pessimistic, producing inappropriately large uncertainties and no point-valued results. While underestimating the uncertainty can lead to misleading information and dangerous system failure without warnings, overly pessimistic uncertainty estimates render the system inoperative for practical purposes as warnings are fired more often. This doctoral thesis aims to study the symbiotic relationship between set-membership-based and probabilistic localization approaches and combine them into a unified hybrid localization approach. This approach enables safe operation while not being overly pessimistic regarding the uncertainty estimation. In the scope of this work, a novel Hybrid Probabilistic- and Set-Membership-based Coarse and Refined (HyPaSCoRe) Localization method is introduced. This method localizes a robot in a building map in real-time and considers two types of hybridizations. On the one hand, set-membership approaches are used to robustify and control probabilistic approaches. On the other hand, probabilistic approaches are used to reduce the pessimism of set-membership approaches by augmenting them with further probabilistic constraints. The method consists of three modules - visual odometry, coarse localization, and refined localization. The HyPaSCoRe Localization uses a stereo camera system, a LiDAR sensor, and GNSS data, focusing on localization in urban canyons where GNSS data can be inaccurate. The visual odometry module computes the relative motion of the vehicle. In contrast, the coarse localization module uses set-membership approaches to narrow down the feasible set of poses and provides the set of most likely poses inside the feasible set using a probabilistic approach. The refined localization module further refines the coarse localization result by reducing the pessimism of the uncertainty estimate by incorporating probabilistic constraints into the set-membership approach. The experimental evaluation of the HyPaSCoRe shows that it maintains the integrity of the uncertainty estimation while providing accurate, most likely point-valued solutions in real-time. Introducing this new hybrid localization approach contributes to developing safe and reliable algorithms in the context of autonomous driving

Glottal-synchronous speech processing

Glottal-synchronous speech processing is a field of speech science where the pseudoperiodicity of voiced speech is exploited. Traditionally, speech processing involves segmenting and processing short speech frames of predefined length; this may fail to exploit the inherent periodic structure of voiced speech which glottal-synchronous speech frames have the potential to harness. Glottal-synchronous frames are often derived from the glottal closure instants (GCIs) and glottal opening instants (GOIs). The SIGMA algorithm was developed for the detection of GCIs and GOIs from the Electroglottograph signal with a measured accuracy of up to 99.59%. For GCI and GOI detection from speech signals, the YAGA algorithm provides a measured accuracy of up to 99.84%. Multichannel speech-based approaches are shown to be more robust to reverberation than single-channel algorithms. The GCIs are applied to real-world applications including speech dereverberation, where SNR is improved by up to 5 dB, and to prosodic manipulation where the importance of voicing detection in glottal-synchronous algorithms is demonstrated by subjective testing. The GCIs are further exploited in a new area of data-driven speech modelling, providing new insights into speech production and a set of tools to aid deployment into real-world applications. The technique is shown to be applicable in areas of speech coding, identification and artificial bandwidth extension of telephone speec