Related papers: Room Impulse Response Estimation using Optimal Tra…
The image-source method is widely applied to compute room impulse responses (RIRs) of shoebox rooms with arbitrary absorption. However, with increasing RIR lengths, the number of image sources grows rapidly, leading to slow computation. In…
In this letter, we investigate the design of multiple reconfigurable intelligent sensing surfaces (RISSs) that enhance both communication and sensing tasks. An RISS incorporates additional active elements tailored to improve sensing…
In this paper, we describe how to efficiently implement an acoustic room simulator to generate large-scale simulated data for training deep neural networks. Even though Google Room Simulator in [1] was shown to be quite effective in…
A method is presented for estimating and reconstructing the sound field within a room using physics-informed neural networks. By incorporating a limited set of experimental room impulse responses as training data, this approach combines…
Active reconfigurable intelligent surfaces (RISs) can improve the performance of integrated sensing and communication (ISAC), and therefore enable simultaneous data transmission and target sensing. However, when the line-of-sight (LoS) link…
Knowing the room geometry may be very beneficial for many audio applications, including sound reproduction, acoustic scene analysis, and sound source localization. Room geometry inference (RGI) deals with the problem of reflector…
Intelligent reflecting surface (IRS) is a novel burgeoning concept, which possesses advantages in enhancing wireless communication and user localization, while maintaining low hardware cost and energy consumption. Herein, we establish an…
Air absorption is an important effect to consider when simulating room acoustics as it leads to significant attenuation in high frequencies. In this study, an offline method for adding air absorption to simulated room impulse responses is…
In the past few years, several case studies have illustrated that the use of occupancy information in buildings leads to energy-efficient and low-cost HVAC operation. The widely presented techniques for occupancy estimation include…
In this paper, we investigate integrated sensing and communication (ISAC) in high-mobility systems with the aid of an intelligent reflecting surface (IRS). To exploit the benefits of Delay-Doppler (DD) spread caused by high mobility,…
In urban driving scenarios, forecasting future trajectories of surrounding vehicles is of paramount importance. While several approaches for the problem have been proposed, the best-performing ones tend to require extremely detailed input…
We introduce a new approach for speech pre-training named SPIRAL which works by learning denoising representation of perturbed data in a teacher-student framework. Specifically, given a speech utterance, we first feed the utterance to a…
Reconstructing high-fidelity magnetic resonance (MR) images from under-sampled k-space is a commonly used strategy to reduce scan time. The posterior sampling of diffusion models based on the real measurement data holds significant promise…
Offline Reinforcement Learning (RL) addresses the problem of sequential decision-making by learning optimal policy through pre-collected data, without interacting with the environment. As yet, it has remained somewhat impractical, because…
We investigate the use of an intelligent reflecting surface (IRS) in a millimeter-wave (mmWave) vehicular communication network. An intelligent reflecting surface consists of passive elements, which can reflect the incoming signals with…
We report the progress in the realization of an electronic / optical simulator for space based, long arm interferometry and its application to the eLISA mission. The goal of this work is to generate realistic optics and electronics signals,…
Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary…
Data availability is essential in the development of acoustic signal processing algorithms, especially when it comes to data-driven approaches that demand large and diverse training datasets. For this reason, an increasing number of…
An environment acoustic model represents how sound is transformed by the physical characteristics of an indoor environment, for any given source/receiver location. Traditional methods for constructing acoustic models involve expensive and…
For line spectrum estimation, we derive the maximum a posteriori probability estimator where prior knowledge of frequencies is modeled probabilistically. Since the spectrum is periodic, an appropriate distribution is the circular von Mises…