Signal Separation Based on Knowledge Representation
The separation of mixed signals typically requires appropriate prior assumptions, while traditional signal separation methods struggle to describe the differences in separation targets with significant features. This paper proposes a signal separation framework based on knowledge representation, whe...
Saved in:
| Main Authors: | Cai Lu, Xuyang Zou, Jingjing Zong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/6/3319 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Upgoing and Downgoing Wavefield Separation in Vertical Seismic Profiling Guided by Signal Knowledge Representation
by: Cai Lu, et al.
Published: (2025-06-01) -
A contrast enhanced representation normalization approach to knowledge distillation
by: Zhiqiang Bao, et al.
Published: (2025-04-01) -
Knowledge‐based representation: Patient engagement in drug development
by: Claudia Egher, et al.
Published: (2024-02-01) -
Dual-context enhanced knowledge representation learning method in hyper-relational knowledge graphs
by: Jiahang Li, et al.
Published: (2025-07-01) -
Blind source separation algorithm for complex signals in noise
by: Feng Pingxing, et al.
Published: (2022-04-01)