I'm currently looking for some preprocessing tutorials for this kind of data. Here are some links to get started:
\nTo be continued ;-)
", "messages": [ { "id": "1372531", "postDate": "07/01/2021 19:25:26", "content": "I'm currently looking for some preprocessing tutorials for this kind of data. Here are some links to get started:
\nTo be continued ;-)
", "rawMarkdown": "I'm currently looking for some preprocessing tutorials for this kind of data. Here are some links to get started:\n\n- https://www.gw-openscience.org/tutorials/\n- https://georgemdallas.wordpress.com/2014/05/14/wavelets-4-dummies-signal-processing-fourier-transforms-and-heisenberg/\n- https://www.gw-openscience.org/GW150914data/GW150914_tutorial.html\n- https://gwpy.github.io/docs/stable/index.html\n- http://doc.ml.tu-berlin.de/bbci/material/publications/Bla_constQ.pdf\n\nTo be continued ;-)", "votes": null }, { "id": "1372759", "postDate": "07/02/2021 02:04:14", "content": "Really helpful resource, Thank you for sharing
", "rawMarkdown": "Really helpful resource, Thank you for sharing", "votes": null }, { "id": "1373108", "postDate": "07/02/2021 08:25:42", "content": "Nice job identifying LIGO resources ;)
", "rawMarkdown": "Nice job identifying LIGO resources ;)", "votes": null }, { "id": "1377531", "postDate": "07/06/2021 00:03:14", "content": "Great guiding resources, Thank you @allunia . Upvoted!
", "rawMarkdown": "Great guiding resources, Thank you @allunia . Upvoted!", "votes": null }, { "id": "1377868", "postDate": "07/06/2021 07:24:50", "content": "Thanks for sharing such useful resources
", "rawMarkdown": "Thanks for sharing such useful resources", "votes": null }, { "id": "1382326", "postDate": "07/09/2021 17:40:49", "content": "One more I find useful together with a paper that can already be found in the discussions:
\nYes, they are useful. Thanks for sharing!
", "rawMarkdown": "Yes, they are useful. Thanks for sharing!", "votes": null }, { "id": "1382704", "postDate": "07/10/2021 07:07:09", "content": "Thanks for sharing!
", "rawMarkdown": "Thanks for sharing!", "votes": null }, { "id": "1383177", "postDate": "07/10/2021 15:38:47", "content": "Great, very useful resources. Thanks for sharing.
", "rawMarkdown": "Great, very useful resources. Thanks for sharing.", "votes": null }, { "id": "1385307", "postDate": "07/12/2021 15:29:02", "content": "Very helpful, thank you.
\nI'm finding the udemy course on signal processing and Fourier Transforms by Mike Cohen incredibly informative as well.
\nAlso, this book on digital signal processing in Python
\n", "rawMarkdown": "Very helpful, thank you. \n\nI'm finding the udemy course on signal processing and Fourier Transforms by Mike Cohen incredibly informative as well.\n- https://www.udemy.com/course/signal-processing\n- https://www.udemy.com/course/fourier-transform-mxc\n\nAlso, this book on digital signal processing in Python\n- [Think DSP by Allen Downey](https://www.amazon.com/gp/product/1491938455/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1)", "votes": null }, { "id": "1385351", "postDate": "07/12/2021 16:17:56", "content": "That Arxiv paper is phenomenal.
\nJust quickly skimming through, I read about the prevalence of pseudo-signals.
\n\n\nFigure 12 shows an example of a glitch. Glitches with power comparable to detectable signals have historically occurred on the order of once per minute, with larger glitches occurring less frequently. Even in their nominal state, the detectors’ data contain glitches introduced by behavior of the instruments or complex interactions between the instruments and their environment. Many of these glitches (but not all) can be associated with transient signals in auxiliary channels from various sensors which serve as “witnesses” to environmental disturbances coupling into the interferometer.
\n
We're going go to have to keep an eye out for these, see how prevalent they are in the data and possibly give them another class to exclude them (or use them as noisy data augmentation).
", "rawMarkdown": "That Arxiv paper is phenomenal. \n\nJust quickly skimming through, I read about the prevalence of pseudo-signals. \n\n> Figure 12 shows an example of a glitch. Glitches with power comparable to detectable signals have historically occurred on the order of once per minute, with larger glitches occurring less frequently. Even in their nominal state, the detectors’ data contain glitches introduced by behavior of the instruments or complex interactions between the instruments and their environment. Many of these glitches (but not all) can be associated with transient signals in auxiliary channels from various sensors which serve as “witnesses” to environmental disturbances coupling into the interferometer.\n\nWe're going go to have to keep an eye out for these, see how prevalent they are in the data and possibly give them another class to exclude them (or use them as noisy data augmentation).", "votes": null }, { "id": "1386671", "postDate": "07/13/2021 16:01:33", "content": "For newbies like me in signal processing competitions, I've found this series of videos on youtube which I think are worth checking out:
\nAfter my experiment, the rof algorithm seems dispensable for this data set?
", "rawMarkdown": "After my experiment, the rof algorithm seems dispensable for this data set?", "votes": null }, { "id": "1392717", "postDate": "07/19/2021 02:56:39", "content": "tx u a lot))))
", "rawMarkdown": "tx u a lot))))", "votes": null }, { "id": "1406357", "postDate": "07/31/2021 17:41:58", "content": "For some one new with signal processing, here is a very clean understandable content
\nContent
\nThanks for sharing! The videos by Valerio are quite amazing!
", "rawMarkdown": "Thanks for sharing! The videos by Valerio are quite amazing!", "votes": null }, { "id": "1457176", "postDate": "08/07/2021 09:24:46", "content": "Many of the same videos in Mike X Cohen's Udemy courses can be found in his Youtube channel. His explanations are very clear. It's worth checking.
", "rawMarkdown": "Many of the same videos in Mike X Cohen's Udemy courses can be found in his Youtube channel. His explanations are very clear. It's worth checking.", "votes": null }, { "id": "1457214", "postDate": "08/07/2021 09:53:40", "content": "Thanks a ton for sharing 😊
", "rawMarkdown": "Thanks a ton for sharing 😊", "votes": null }, { "id": "1463838", "postDate": "08/10/2021 10:54:04", "content": "I'm trying to reproduce the denoising procedure, but I cannot find in their notebook (https://www.uv.es/virgogroup/Denoising_ROF.html) the definition of a function gs1 they make use of.
strain_H1_TV=gs1(strain_H1_filt,1,1,0.2,0.01)\nstrain_L1_TV=gs1(strain_L1_filt,1,1,0.2,0.01)\n\n
Anyone has an idea of what it is?
", "rawMarkdown": "I'm trying to reproduce the denoising procedure, but I cannot find in their notebook (https://www.uv.es/virgogroup/Denoising_ROF.html) the definition of a functiongs1 they make use of. \n\n\nstrain_H1_TV=gs1(strain_H1_filt,1,1,0.2,0.01)\nstrain_L1_TV=gs1(strain_L1_filt,1,1,0.2,0.01)\n\nAnyone has an idea of what it is?", "votes": null }, { "id": "1478199", "postDate": "08/17/2021 21:03:11", "content": "
Did you ever find teh definition for the ROF function gs1
", "rawMarkdown": "Did you ever find teh definition for the ROF function gs1", "votes": null }, { "id": "1479665", "postDate": "08/18/2021 15:16:36", "content": "No. No one has answered.
", "rawMarkdown": "No. No one has answered.", "votes": null }, { "id": "1480270", "postDate": "08/18/2021 23:14:21", "content": "@zhangeng can you share the implementation of the algorithm. I'm unable to find anything online
", "rawMarkdown": "zhangeng can you share the implementation of the algorithm. I'm unable to find anything online", "votes": null }, { "id": "1561217", "postDate": "10/27/2021 12:20:47", "content": "Hey All,
\nThank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.
\nThank you all,
\nRegards,
\nChris
Nice Work.
", "rawMarkdown": "Nice Work.", "votes": null }, { "id": "2850589", "postDate": "06/02/2024 08:26:41", "content": "How can I converted into wavelets instead of generating spectrogram and the wavelet is feed into the cnn model
", "rawMarkdown": "How can I converted into wavelets instead of generating spectrogram and the wavelet is feed into the cnn model", "votes": null } ], "comments": [ { "id": 1372759, "author_name": "samarthgupta39", "author_url": "", "post_date": "07/02/2021 02:04:14", "content": "Really helpful resource, Thank you for sharing
", "votes": null, "replies": [] }, { "id": 1373108, "author_name": "zerafachris", "author_url": "", "post_date": "07/02/2021 08:25:42", "content": "Nice job identifying LIGO resources ;)
", "votes": null, "replies": [] }, { "id": 1377531, "author_name": "mustafasenol95", "author_url": "", "post_date": "07/06/2021 00:03:14", "content": "Great guiding resources, Thank you @allunia . Upvoted!
", "votes": null, "replies": [] }, { "id": 1377868, "author_name": "sandraphari", "author_url": "", "post_date": "07/06/2021 07:24:50", "content": "Thanks for sharing such useful resources
", "votes": null, "replies": [] }, { "id": 1382326, "author_name": "allunia", "author_url": "", "post_date": "07/09/2021 17:40:49", "content": "One more I find useful together with a paper that can already be found in the discussions:
\nYes, they are useful. Thanks for sharing!
", "votes": null, "replies": [] }, { "id": 1385351, "author_name": "tpmeli", "author_url": "", "post_date": "07/12/2021 16:17:56", "content": "That Arxiv paper is phenomenal.
\nJust quickly skimming through, I read about the prevalence of pseudo-signals.
\n\n\nFigure 12 shows an example of a glitch. Glitches with power comparable to detectable signals have historically occurred on the order of once per minute, with larger glitches occurring less frequently. Even in their nominal state, the detectors’ data contain glitches introduced by behavior of the instruments or complex interactions between the instruments and their environment. Many of these glitches (but not all) can be associated with transient signals in auxiliary channels from various sensors which serve as “witnesses” to environmental disturbances coupling into the interferometer.
\n
We're going go to have to keep an eye out for these, see how prevalent they are in the data and possibly give them another class to exclude them (or use them as noisy data augmentation).
", "votes": null, "replies": [] }, { "id": 1387644, "author_name": "zhangeng", "author_url": "", "post_date": "07/14/2021 10:46:24", "content": "After my experiment, the rof algorithm seems dispensable for this data set?
", "votes": null, "replies": [] }, { "id": 1463838, "author_name": "jcesquiveld", "author_url": "", "post_date": "08/10/2021 10:54:04", "content": "I'm trying to reproduce the denoising procedure, but I cannot find in their notebook (https://www.uv.es/virgogroup/Denoising_ROF.html) the definition of a function gs1 they make use of.
strain_H1_TV=gs1(strain_H1_filt,1,1,0.2,0.01)\nstrain_L1_TV=gs1(strain_L1_filt,1,1,0.2,0.01)\n\n
Anyone has an idea of what it is?
", "votes": null, "replies": [] }, { "id": 1478199, "author_name": "kevinmcisaac", "author_url": "", "post_date": "08/17/2021 21:03:11", "content": "Did you ever find teh definition for the ROF function gs1
", "votes": null, "replies": [] }, { "id": 1479665, "author_name": "jcesquiveld", "author_url": "", "post_date": "08/18/2021 15:16:36", "content": "No. No one has answered.
", "votes": null, "replies": [] }, { "id": 1480270, "author_name": "kevinmcisaac", "author_url": "", "post_date": "08/18/2021 23:14:21", "content": "@zhangeng can you share the implementation of the algorithm. I'm unable to find anything online
", "votes": null, "replies": [] } ] }, { "id": 1382704, "author_name": "rahulnm13", "author_url": "", "post_date": "07/10/2021 07:07:09", "content": "Thanks for sharing!
", "votes": null, "replies": [] }, { "id": 1383177, "author_name": "vinayakshanawad", "author_url": "", "post_date": "07/10/2021 15:38:47", "content": "Great, very useful resources. Thanks for sharing.
", "votes": null, "replies": [] }, { "id": 1385307, "author_name": "tpmeli", "author_url": "", "post_date": "07/12/2021 15:29:02", "content": "Very helpful, thank you.
\nI'm finding the udemy course on signal processing and Fourier Transforms by Mike Cohen incredibly informative as well.
\nAlso, this book on digital signal processing in Python
\n", "votes": null, "replies": [ { "id": 1457176, "author_name": "jcesquiveld", "author_url": "", "post_date": "08/07/2021 09:24:46", "content": "Many of the same videos in Mike X Cohen's Udemy courses can be found in his Youtube channel. His explanations are very clear. It's worth checking.
", "votes": null, "replies": [] } ] }, { "id": 1386671, "author_name": "jcesquiveld", "author_url": "", "post_date": "07/13/2021 16:01:33", "content": "For newbies like me in signal processing competitions, I've found this series of videos on youtube which I think are worth checking out:
\nThanks for sharing! The videos by Valerio are quite amazing!
", "votes": null, "replies": [] } ] }, { "id": 1392717, "author_name": "tienti", "author_url": "", "post_date": "07/19/2021 02:56:39", "content": "tx u a lot))))
", "votes": null, "replies": [] }, { "id": 1406357, "author_name": "harshitlakhani", "author_url": "", "post_date": "07/31/2021 17:41:58", "content": "For some one new with signal processing, here is a very clean understandable content
\nContent
\nThanks a ton for sharing 😊
", "votes": null, "replies": [] }, { "id": 1561217, "author_name": "zerafachris", "author_url": "", "post_date": "10/27/2021 12:20:47", "content": "Hey All,
\nThank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.
\nThank you all,
\nRegards,
\nChris
Nice Work.
", "votes": null, "replies": [] }, { "id": 2850589, "author_name": "vyshnavkp", "author_url": "", "post_date": "06/02/2024 08:26:41", "content": "How can I converted into wavelets instead of generating spectrogram and the wavelet is feed into the cnn model
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1372531": "I'm currently looking for some preprocessing tutorials for this kind of data. Here are some links to get started:\n\n- https://www.gw-openscience.org/tutorials/\n- https://georgemdallas.wordpress.com/2014/05/14/wavelets-4-dummies-signal-processing-fourier-transforms-and-heisenberg/\n- https://www.gw-openscience.org/GW150914data/GW150914_tutorial.html\n- https://gwpy.github.io/docs/stable/index.html\n- http://doc.ml.tu-berlin.de/bbci/material/publications/Bla_constQ.pdf\n\nTo be continued ;-)", "1372759": "Really helpful resource, Thank you for sharing", "1373108": "Nice job identifying LIGO resources ;)", "1377531": "Great guiding resources, Thank you @allunia . Upvoted!", "1377868": "Thanks for sharing such useful resources", "1382326": "One more I find useful together with a paper that can already be found in the discussions:\n\n- https://www.uv.es/virgogroup/Denoising_ROF.html (code)\n- https://arxiv.org/pdf/1908.11170.pdf (paper)", "1382556": "Yes, they are useful. Thanks for sharing!", "1382704": "Thanks for sharing!", "1383177": "Great, very useful resources. Thanks for sharing.", "1385307": "Very helpful, thank you. \n\nI'm finding the udemy course on signal processing and Fourier Transforms by Mike Cohen incredibly informative as well.\n- https://www.udemy.com/course/signal-processing\n- https://www.udemy.com/course/fourier-transform-mxc\n\nAlso, this book on digital signal processing in Python\n- [Think DSP by Allen Downey](https://www.amazon.com/gp/product/1491938455/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1)", "1385351": "That Arxiv paper is phenomenal. \n\nJust quickly skimming through, I read about the prevalence of pseudo-signals. \n\n> Figure 12 shows an example of a glitch. Glitches with power comparable to detectable signals have historically occurred on the order of once per minute, with larger glitches occurring less frequently. Even in their nominal state, the detectors’ data contain glitches introduced by behavior of the instruments or complex interactions between the instruments and their environment. Many of these glitches (but not all) can be associated with transient signals in auxiliary channels from various sensors which serve as “witnesses” to environmental disturbances coupling into the interferometer.\n\nWe're going go to have to keep an eye out for these, see how prevalent they are in the data and possibly give them another class to exclude them (or use them as noisy data augmentation).", "1386671": "For newbies like me in signal processing competitions, I've found this series of videos on youtube which I think are worth checking out:\n\ngs1 they make use of. \n\n\nstrain_H1_TV=gs1(strain_H1_filt,1,1,0.2,0.01)\nstrain_L1_TV=gs1(strain_L1_filt,1,1,0.2,0.01)\n\nAnyone has an idea of what it is?", "1478199": "Did you ever find teh definition for the ROF function gs1", "1479665": "No. No one has answered.", "1480270": "zhangeng can you share the implementation of the algorithm. I'm unable to find anything online", "1561217": "Hey All,\n\nThank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.\n\nThank you all,\n\nRegards,\nChris", "2772318": "Nice Work.", "2850589": "How can I converted into wavelets instead of generating spectrogram and the wavelet is feed into the cnn model" }, "source": "meta" }