Signal denoising based on the Schrödinger operator's eigenspectrum and a curvature constraint
Abstract The authors propose an adaptive, general and data‐driven curvature penalty for signal denoising via the Schrödinge operator. The term is derived by assuming noise to be generally Gaussian distributed, a widely applied assumption in most 1D signal denoising applications. The proposed penalty...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-05-01
|
| Series: | IET Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/sil2.12023 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|