Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2208.12984 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- The effect of the sample radius on the total photoacoustic signal processed by neural networks trained with undistorded and distorded signals is carefully analized for modulation frequencies from 20 to 20 kHz. This is done for signals generated for a 400micrometers thick Si n-type plate, whose radius varies from 2 to 7 mm. It is found that the networks trained with both undistorded or distorded signals yield the best predictions for sample radii between 2 and 3 mm, which is close to the used microphone aperture radius of 1.5 mm. The network trained only with undistorted signals gives the best results for sample radii comparable to the microphone dimensions. The obtained results justify the validity of a theoretical model derived for a sample radius equals to the microphone aperture and indicate the experimental necessity to use samples with radii comparable to this aperture.