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Acado Toolkit solvers testing

A deep learning auto-regressive method is trained to learn the acoustic propagation in presence of obstacles. The method is flexible to account for both far-fields prediction (non-reflecting cases) as well as duct acoustics (non-reflecting BCs).

Copy of the original CREME project scripts. This copy is used to learn the functioning of the original simulations and modify it.

Reproducibility study of a multiscale CNN used for modelling PDE's

Library for performing acoustic beamforming from signal obtained with an array of microphones.

Effects of Boundary Conditions in Fully Convolutional Networks for Learning Spatio-temporal Dynamics

[ISAE-SUPAERO] (Chamal PERERA - Guillaume ROUX)

[UPM] - Radiation module

[UC3M] activity profile tool designer