Fakultät 07 / Institut für Nachrichtentechnik
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High-quality rendering of spatial sound fields in real-time is becoming increasingly important with the steadily growing interest in virtual and augmented reality technologies. Typically, a spherical microphone array (SMA) is used to capture a spatial sound field. The captured sound field can be reproduced over headphones in real-time using binaural rendering, virtually placing a single listener in the sound field. Common methods for binaural rendering first spatially encode the sound field by transforming it to the spherical harmonics domain and then decode the sound field binaurally by combining it with head-related transfer functions (HRTFs). However, these rendering methods are computationally demanding, especially for high-order SMAs, and require implementing quite sophisticated real-time signal processing. This paper presents a computationally more efficient method for real-time binaural rendering of SMA signals by linear filtering. The proposed method allows representing any common rendering chain as a set of precomputed finite impulse response filters, which are then applied to the SMA signals in real-time using fast convolution to produce the binaural signals. Results of the technical evaluation show that the presented approach is equivalent to conventional rendering methods while being computationally less demanding and easier to implement using any real-time convolution system. However, the lower computational complexity goes along with lower flexibility. On the one hand, encoding and decoding are no longer decoupled, and on the other hand, sound field transformations in the SH domain can no longer be performed. Consequently, in the proposed method, a filter set must be precomputed and stored for each possible head orientation of the listener, leading to higher memory requirements than the conventional methods. As such, the approach is particularly well suited for efficient real-time binaural rendering of SMA signals in a fixed setup where usually a limited range of head orientations is sufficient, such as live concert streaming or VR teleconferencing.
We study p-adic L-functions Lp(s, 휒) for Dirichlet characters 휒. We show that Lp(s, 휒) has a Dirichlet series expansion for each regularization parameter c that is prime to p and the conductor of 휒. The expansion is proved by transforming a known formula for p-adic L-functions and by controlling the limiting behavior. A fnite number of Euler factors can be factored of in a natural manner from the p-adic Dirichlet series. We also provide an alternative proof of the expansion using p-adic measures and give an explicit formula for the values of the regularized Bernoulli distribution. The result is particularly simple for c = 2, where we obtain a Dirichlet series expansion that is similar to the complex case.
The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.
Untersuchung der Yosys Hardwaresynthese von der internen Datenstruktur RTLIL bis zur Netzliste
(2023)
Das Ziel dieser Arbeit ist die Beantwortung der Frage "Wie funktioniert Synthese?". Yosys ist ein offenes Synthesewerkzeug, welches untersucht wurde, um diese Frage zu beantworten. Yosys implementiert eine Datenstruktur RTLIL, mit der ein Entwurf in allen Synthesephasen dargestellt wird. Yosys ist modular aufgebaut, was dem Nutzer ermöglicht, das Programm zu erweitern. Die Synthese in Yosys ist auf Pässe unterteilt, die jeweils eine bestimmte Aufgabe erfüllen. Im Rahmen der Arbeit wurde die Datenstruktur und die Passes im einzelnen analysiert. Es wurde auch untersucht, wie in Yosys Erweiterungen zu implementieren sind. Die Analyse hat gezeigt, dass ein wichtiger Teil der Synthese die Umwandlung von Prozessen in eine RTL-Beschreibung darstellt. Im Rahmen der Synthese werden die, von einem Frontend vorläufig erzeugten RTL-Komponenten, umgewandelt. Der letzte Schritt der Synthese ist das Technologiemapping, welches die umgewandelten Komponente auf die verwendete Hardware anpasst.
Conventional individual head-related transfer function (HRTF) measurements are demanding in terms of measurement time and equipment. For more flexibility, free body movement (FBM) measurement systems provide an easy-to-use way to measure full-spherical HRTF datasets with less effort. However, having no fixed measurement installation implies that the HRTFs are not sampled on a predefined regular grid but rely on the individual movements of the subject. Furthermore, depending on the measurement effort, a rather small number of measurements can be expected, ranging, for example, from 50 to 150 sampling points. Spherical harmonics (SH) interpolation has been extensively studied recently as one method to obtain full-spherical datasets from such sparse measurements, but previous studies primarily focused on regular full-spherical sampling grids. For irregular grids, it remains unclear up to which spatial order meaningful SH coefficients can be calculated and how the resulting interpolation error compares to regular grids. This study investigates SH interpolation of selected irregular grids obtained from HRTF measurements with an FBM system. Intending to derive general constraints for SH interpolation of irregular grids, the study analyzes how the variation of the SH order affects the interpolation results. Moreover, the study demonstrates the importance of Tikhonov regularization for SH interpolation, which is popular for solving ill-posed numerical problems associated with such irregular grids. As a key result, the study shows that the optimal SH order that minimizes the interpolation error depends mainly on the grid and the regularization strength but is almost independent of the selected HRTF set. Based on these results, the study proposes to determine the optimal SH order by minimizing the interpolation error of a reference HRTF set sampled on the sparse and irregular FBM grid. Finally, the study verifies the proposed method for estimating the optimal SH order by comparing interpolation results of irregular and equivalent regular grids, showing that the differences are small when the SH interpolation is optimally parameterized.
Das Ziel der vorliegenden Arbeit besteht darin, die Frage zu beantworten wie Yosys Verilog einliest und daraus RTLIL generiert. Mit der Beantwortung dieser Frage, soll die Datenstruktur RTLIL und die Verknüpfung zu einem Verilog Design besser verstanden werden. Dafür wurde das Frontend von Yosys untersucht und die Datenstruktur RTLIL näher eleuchtet. Als Ergebnis konnte festgehalten werden, dass die AstNode Datenstruktur eine wesentliche Rolle bei der Konvertierung von Verilog zu RTLIL spielt, und mit deren Hilfe beim Einlesen ein abstrakter Syntaxbaum gebildet wird. Allein der Typ des Knotens beeinflusst, wie der RTLIL Generator damit umgeht. Weiter ist die Generierung von RTLIL::Cell Objekten als erster Schritt zur Synthese zu verstehen, da sie durch Technologie Mapping reale Komponenten abbilden können
This project was done in collaboration with CERN and is part of the detector control system of the ATLAS experiment. The primary goal foresaw the development and testing of the FPGA card for the MOPS-HUB crate with the focus on radiation tolerance. This was accomplished with the approach of designing two different PCBs. The first PCB was created as a fast prototype with the use of a commercial SOM-board. This was also beneficial for confirming that the chosen FPGA is suitable for the MOPS-HUB application. After the successful assembly and test, a second, more complex and foremost radiation tolerant PCB was designed. This was achieved by solely using components of the CERN radiation database.
The second part of this thesis focuses on increasing the distance of TMR registers with a Python script. A method was created for extracting and later parsing a design’s placement
information from Vivado. Furthermore, were system designed and implemented to recognize TMR cells, to find and validate free cells and to finally create a new placement for import into Vivado. These algorithms were tested with a multitude of configurations and the quality, based on the maximum possible frequency of a design, determined.
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
For most classes of chains, it is known if these contain locks, but especially for fixed-angle equilateral equiangular obtuse open polygonal chains in 3D, which can be used to model protein backbones, this is unknown. Fixed-angle equilateral equiangular obtuse closed and open polygonal chains can be used to model polymers. For these, it is clear, that locks based on knots exist, but not which chains are generally locked. We therefore examine both open and closed fixed-angle equilateral equiangular obtuse chains. For this purpose, those chains are divided into various subgroups and, depending on the subgroup, other aspects are investigated to show locks. Techniques from knot theory, graph theory, and specifically robot arm reachability and motion planning are combined. Algorithms are developed to create chains in desired configurations and to study them. It is shown why all fixed-angle equilateral equiangular obtuse closed chains are expected to be locked or in rare cases rigid and non-locked, but never non-locked and non-rigid. For fixed-angle equilateral equiangular obtuse open chains it is shown why it is expected that there are open chains that are locked and that the smallest locked open chain has 𝑛=7.
A test tool for Langton's ant-based algorithms is created. Among other things, it can create test files for the NIST-Statistical-Test-Suite. The test tool is used to investigate the invertibility, ring formation and randomness of 7 created models which are extensions of Langton’s ant. The models are examined to possibly use them as pseudo-random generator (PRG) or block cipher. All models use memories which are based on tori. This property is central, because this is how rings are formed in the first place and in addition the behavior of all models at the physical boundaries of the memory is clearly defined in this way. The different models have special properties which are also investigated. These include variable color sets, discrete convolution, multidimensionality, and the use of multiple ants, which are arranged fractal hierarchically and influence each other. The extensions convolution, multidimensional scalable and multidimensional scalable fractal ant colony are presented here for the first time. It is shown that well-chosen color sets and high-dimensional tori are particularly well suited as a basis for Langton's ant based PRGs. In addition, it is shown that a block cipher can be generated on this basis.