118 research outputs found

    Machine Learning and Signal Processing Design for Edge Acoustic Applications

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    Machine Learning and Signal Processing Design for Edge Acoustic Applications

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    Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance

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    The pervasive nature of wireless telecommunication has made it the foundation for mainstream technologies like automation, smart vehicles, virtual reality, and unmanned aerial vehicles. As these technologies experience widespread adoption in our daily lives, ensuring the reliable performance of cellular networks in mobile scenarios has become a paramount challenge. Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages and implications. Notably, the study presents an impressive 53% improvement in signal-to-noise ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and Zero forcing (ZF) techniques, alongside deep neural networks (DNN) employing Bayesian Optimization (BO), represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino, in enabling location-aware beamforming

    Current advancements of numerical methods and experimental means for the integration of future propulsion systems.

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    To integrate advanced propulsion systems and to assess and verify the related benefit (e.g. fuel burn, noise) suitable design, evaluation and measurement tools are required. For that reason, the so-called Cross-Capability-Demonstrator (XDC) has been set up as one major activity of the Large Passenger Aircraft (LPA) Platform 1 of the Clean Sky 2 initiative. The XDC is intended to demonstrate high-fidelity CFD-tools, further developed prediction tools for noise and aero-elastics as well as advanced testing tools for measuring e.g. the flow field, the deformation and the acoustics. The article will provide an update on activities within the XDC and presents some examples of recent accomplishments related to this demonstrator

    An Anchor-Point Based Image-Model for Room Impulse Response Simulation with Directional Source Radiation and Sensor Directivity Patterns

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    The image model method has been widely used to simulate room impulse responses and the endeavor to adapt this method to different applications has also piqued great interest over the last few decades. This paper attempts to extend the image model method and develops an anchor-point-image-model (APIM) approach as a solution for simulating impulse responses by including both the source radiation and sensor directivity patterns. To determine the orientations of all the virtual sources, anchor points are introduced to real sources, which subsequently lead to the determination of the orientations of the virtual sources. An algorithm is developed to generate room impulse responses with APIM by taking into account the directional pattern functions, factional time delays, as well as the computational complexity. The developed model and algorithms can be used in various acoustic problems to simulate room acoustics and improve and evaluate processing algorithms.Comment: 19 pages, 8 figure

    Design of large polyphase filters in the Quadratic Residue Number System

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    雑音特性の変動を伴う多様な環境で実用可能な音声強調

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    筑波大学 (University of Tsukuba)201
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