A data-driven method for automated data superposition with applications in soft matter science
The superposition of data sets with internal parametric self-similarity is a longstanding and widespread technique for the analysis of many types of experimental data across the physical sciences. Typically, this superposition is performed manually, or recently through the application of one of a fe...
| Main Authors: | , , |
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| Format: | Article |
| Language: | en_US |
| Published: |
Cambridge University Press (CUP)
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/1721.1/153486 |