A Proposal of an End-to-End DoA Estimation System Aided by Deep Learning.
Daniel Akira AndoToshihiko NishimuraTakanori SatoTakeo OhganeYasutaka OgawaJunichiro HagiwaraPublished in: WPMC (2022)
Keyphrases
- end to end
- deep learning
- doa estimation
- direction of arrival
- multipath
- antenna array
- canonical correlation analysis
- unsupervised learning
- machine learning
- weakly supervised
- mental models
- congestion control
- ad hoc networks
- computer vision
- estimation error
- real time
- signal to noise ratio
- least squares
- similarity measure
- sound source
- feature selection