PINN-for-HRTF-upsampling

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PINN-for-HRTF-upsampling

(★ 10)

A physics-informed neural network method for head-related transfer function upsampling

PINN-for-HRTF-upsampling 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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This is the source code for paper

"Spatial Upsampling of Head-Related Transfer Functions Using a Physics-Informed Neural Network"
which is also attached here as a PDF file.

Sec. V, the interpolation experiment

Read pinn.py and see the result shown in  'interpolation.png' and 'interpolation.fig'

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Or you can run the code and generate the result by yourself:

0, Download all files into one folder;

1, start a python terminal;

2, go to the same folder;

3, run the code by exec(open('pinn.py').read());

4, pinn.py will read the 40.mat file and generate the 40_L3.mat.

Trained on one cpu core of Macbook M1 pro, the runtime was about 7 hours.  
The runtime can be significantly reduced with more cpu cores.

5, Start Matlab, and go to the same folder, run the 'result.m' file, then you will get the figures.

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PINN-for-HRTF-upsampling

PINN-for-HRTF-upsampling 최신버젼 다운로드

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PINN-for-HRTF-upsampling 최신버젼 다운로드

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