| Predicate |
Object |
| contentType |
Journal Article |
| endingPage |
58 |
| issn |
2662-8457 |
| issueIdentifier |
1 |
| pageRange |
47-58 |
| publicationName |
Nature Computational Science |
| startingPage |
47 |
| bibliographicCitation |
Arts LPA, van den Broek EL. The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time–frequency analysis. Nature Computational Science. 2022 Jan 01;2(1):47–58. doi: 10.1038/s43588-021-00183-z. |
| creator |
http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0002-2017-0141
http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0001-8398-0259 |
| date |
2022-01-27^^<http://www.w3.org/2001/XMLSchema#date> |
| identifier |
https://pubmed.ncbi.nlm.nih.gov/PMC10766549
https://doi.org/10.1038/s43588-021-00183-z
https://pubmed.ncbi.nlm.nih.gov/38177705 |
| isPartOf |
http://rdf.ncbi.nlm.nih.gov/pubchem/journal/50330
https://portal.issn.org/resource/ISSN/2662-8457 |
| language |
English |
| source |
https://www.crossref.org/
https://pubmed.ncbi.nlm.nih.gov/
https://scigraph.springernature.com/ |
| title |
The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time–frequency analysis |