相关论文: Simulating Multi-channel Wind Noise Based on the C…
In this work, we investigate direction finding in the presence of sensor gain uncertainties and directional perturbations for sensor array processing in a multi-frequency scenario. Specifically, we adopt a distributed optimization scheme in…
The efficacy of active noise control technology in mitigating urban noise, particularly in relation to low-frequency components, has been well-established. In the realm of traditional academic research, adaptive algorithms, such as the…
Distributed multichannel active noise control (DMCANC) systems assign the high computational load of conventional centralized algorithms across multiple processing nodes, leveraging inter-node communication to collaboratively suppress…
Advancing quantum technologies necessitates an in-depth exploration of how operations generate quantum resources and respond to noise. Crucial are gates generating quantum coherence and the challenge of mitigating gate dephasing noise.…
This work develops a theoretical model for steady thermodynamic and kinematic profiles for severe convective storm environments, building off of the two-layer static energy framework developed in Agard and Emanuel (2017). The model is…
This paper introduces two new algorithms to accurately estimate the process noise covariance of a discrete-time Kalman filter online for robust orbit determination in the presence of dynamics model uncertainties. Common orbit determination…
Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes the benchmark…
In this work we extend a multi-qubit benchmarking technique known as the Binned Output Generation (BOG) in order to discriminate between coherent and incoherent noise sources in the multi-qubit regime. While methods exist to discriminate…
The fundamental equations that model turbulent flow do not provide much insight into the size and shape of observed turbulent structures. We investigate the efficient and accurate representation of structures in two-dimensional turbulence…
The generation and storage of spin squeezing is an attracting topic in quantum metrology and the foundations of quantum mechanics. The major models to realize the spin squeezing are the one- and two-axis twisting models. Here, we consider a…
Time-varying linear state-space models are powerful tools for obtaining mathematically interpretable representations of neural signals. For example, switching and decomposed models describe complex systems using latent variables that evolve…
A semi-empirical acoustic model for self-noise was adapted to predict the sound radiated from an axial fan featuring rotating controlled diffusion blades (RCDB). Experimental data for wake velocity, mass flow rate across the fan, and fan…
The problem of locating an odor source in turbulent flows is central to key applications such as environmental monitoring and disaster response. We address this challenge by designing an algorithm based on Bayesian inference, which uses…
Statistical downscaling is a crucial component of the weather modeling field, where high-resolution outputs must be reconstructed from coarse-resolution inputs with the full cost of dynamical refinement. In this work, we investigate a…
We have developed a full model to simulate spherical detectors where all main sources of noise are considered. We have built a computer code for determining the source direction and the wave polarization (solution of the inverse problem) in…
We demonstrate the existence of noise-induced periodicity (coherence resonance) in both a discrete-time model and a continuous-time model of an excitable neuron. In particular, we show that the effects of noise added to the fast and slow…
Aerodynamic noise is a limitation for further exploitation of wind energy resources. As this type of noise is caused by the interaction of turbulent flow with the airframe, a detailed resolution of the flow is necessary to obtain an…
In this paper we introduce the idea of multi-view networks for sound classification with multiple sensors. We show how one can build a multi-channel sound recognition model trained on a fixed number of channels, and deploy it to scenarios…
From the flashes of fireflies to Josephson junctions and power infrastructure, networks of coupled phase oscillators provide a powerful framework to describe synchronization phenomena in many natural and engineered systems. Most real-world…
Sound recordings are used in various ecological studies, including acoustic wildlife monitoring. Such surveys require automatic detection of target sound events. However, current detectors, especially those relying on band-limited energy,…