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| Natura: | Preprint |
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2026
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| Accesso online: | https://arxiv.org/abs/2604.13084 |
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| _version_ | 1866914473269264384 |
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| author | Vacher, Marc Perrard, Stéphane Ramananarivo, Sophie |
| author_facet | Vacher, Marc Perrard, Stéphane Ramananarivo, Sophie |
| contents | This work presents the application of the Complex Orthogonal Decomposition (C.O.D.) to a simple spatio-temporal signal. C.O.D. has been introduced rst in the article of B. Feeny, entitled "A Complex Orthogonal Decomposition for Wave Motion Analysis" [1], published in the Journal of Sound and Vibration. The purpose of this signal analysis method is to extract spatial and temporal modes out of a signal. This approach is especially suited to deal with oscillatory signals where phase information is important and where spatial forms are unknown. We provide two theoretical chapters presenting the main mathematical concepts behind C.O.D. and a series of example (with associated Python scripts) to demonstrate the e ciency of the method and some characteristical features. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_13084 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Complex Orthogonal Decomposition (C.O.D.) using Python Vacher, Marc Perrard, Stéphane Ramananarivo, Sophie Signal Processing This work presents the application of the Complex Orthogonal Decomposition (C.O.D.) to a simple spatio-temporal signal. C.O.D. has been introduced rst in the article of B. Feeny, entitled "A Complex Orthogonal Decomposition for Wave Motion Analysis" [1], published in the Journal of Sound and Vibration. The purpose of this signal analysis method is to extract spatial and temporal modes out of a signal. This approach is especially suited to deal with oscillatory signals where phase information is important and where spatial forms are unknown. We provide two theoretical chapters presenting the main mathematical concepts behind C.O.D. and a series of example (with associated Python scripts) to demonstrate the e ciency of the method and some characteristical features. |
| title | Complex Orthogonal Decomposition (C.O.D.) using Python |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2604.13084 |