activity
20152023
most citedMachine learning in acoustics: theory and applications

574 citations · 2k across the 28 of their papers we have counts for

collaborators

28 papers

math.ST2023

Robust and Sparse M-Estimation of DOA

Christoph F. Mecklenbräuker, Peter Gerstoft, Esa Ollila +1

A robust and sparse Direction of Arrival (DOA) estimator is derived for array data that follows a Complex Elliptically Symmetric (CES) distribution with zero-mean and finite second…

cs.LG2022★ 1 cited

Spoofing Attack Detection in the Physical Layer with Commutative Neural Networks

Daniel Romero, Peter Gerstoft, Hadi Givehchian +1

In a spoofing attack, an attacker impersonates a legitimate user to access or tamper with data intended for or produced by the legitimate user. In wireless communication systems, t…

cs.SD2022

Deep Learning Object Detection Approaches to Signal Identification

Luke Wood, Kevin Anderson, Peter Gerstoft +3

Traditionally source identification is solved using threshold based energy detection algorithms. These algorithms frequently sum up the activity in regions, and consider regions ab…

eess.SP2022★ 14 cited

Graph-based sequential beamforming

Yongsung Park, Florian Meyer, Peter Gerstoft

This paper presents a Bayesian estimation method for sequential direction finding. The proposed method estimates the number of directions of arrivals (DOAs) and their DOAs performi…

eess.SP2022★ 54 cited

Gridless DOA Estimation with Multiple Frequencies

Yifan Wu, Michael B. Wakin, Peter Gerstoft

Direction-of-arrival (DOA) estimation is widely applied in acoustic source localization. A multi-frequency model is suitable for characterizing the broadband structure in acoustic…

cs.SD2021★ 13 cited

Audio scene monitoring using redundant ad-hoc microphone array networks

Peter Gerstoft, Yihan Hu, Michael J. Bianco +4

We present a system for localizing sound sources in a room with several ad-hoc microphone arrays. Each circular array performs direction of arrival (DOA) estimation independently u…