Feasibility study for the automation of environmental noise contamination detection for community noise fly-over testing

[1]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[2]  Trevor Hastie,et al.  An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.

[3]  Ping Zhang.  Model Selection Via Multifold Cross Validation , 1993 .

[4]  Donald P. Percival,et al.  On estimation of the wavelet variance , 1995 .

[5]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[7]  Amara Lynn Graps,et al.  An introduction to wavelets , 1995 .

[8]  Michael G. Jones,et al.  Flight Test Methodology for NASA Advanced Inlet Liner on 737MAX-7 Test Bed (Quiet Technology Demonstrator 3) , 2019, 25th AIAA/CEAS Aeroacoustics Conference.

[9]  Stefan Uellenberg,et al.  The Quiet Technology Demonstrator Program: Flight Validation of Airplane Noise-Reduction Concepts , 2006 .

[10]  Benjamin Schrauwen,et al.  End-to-end learning for music audio , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  Ali N. Akansu,et al.  Emerging applications of wavelets: A review , 2010, Phys. Commun..

[12]  Min Zhou,et al.  ECG Classification Using Wavelet Packet Entropy and Random Forests , 2016, Entropy.

[13]  Joakim Andén,et al.  Deep Scattering Spectrum , 2013, IEEE Transactions on Signal Processing.

[14]  A.N. Akansu.  Wavelets and filter banks. A signal processing perspective , 1994, IEEE Circuits and Devices Magazine.