Comments (12)
AFAIK nobody is working on this
just be careful that filters you use are zero-phase
from mne-python.
Another option is to adapt the line filtering routines from Chronux, as they don't require the use of band-stop filters.
from mne-python.
heard this one before on the mailing list (probably you mentioned it:)
I should look into it once more.
thanks for the (re)pointer
On 24.10.2012, at 23:54, Eric89GXL [email protected] wrote:
Another option is to adapt the line filtering routines from Chronux, as they don't require the use of band-stop filters.
—
Reply to this email directly or view it on GitHub.
from mne-python.
Basically it uses multi-taper estimation combined with an F statistic to infer if there were significant sinusoidal components in the data. You can even specifically tell it which frequencies to test, which is nice because you could restrict it to the line freq and its harmonics. I haven't personally tried it on M/EEG data, though...
from mne-python.
sounds cool.
would be good however
On 25.10.2012, at 00:07, Eric89GXL [email protected] wrote:
Basically it uses multi-taper estimation combined with an F statistic to infer if there were significant sinusoidal components in the data. You can even specifically tell it which frequencies to test, which is nice because you could restrict it to the line freq and its harmonics. I haven't personally tried it on M/EEG data, though...
—
Reply to this email directly or view it on GitHub.
from mne-python.
woops, sorry, something was missing--
would be good to have one or two references from meeg studies using this technique.
but anyways, sounds very nice.
let me look into this soon.
D
On 25.10.2012, at 00:14, "Denis A. Engemann" [email protected] wrote:
sounds cool.
would be good howeverOn 25.10.2012, at 00:07, Eric89GXL [email protected] wrote:
Basically it uses multi-taper estimation combined with an F statistic to infer if there were significant sinusoidal components in the data. You can even specifically tell it which frequencies to test, which is nice because you could restrict it to the line freq and its harmonics. I haven't personally tried it on M/EEG data, though...
—
Reply to this email directly or view it on GitHub.
from mne-python.
Just a reminder to @agramfort to look into notch filtering for 0.6, as our code could easily knock out a small band of frequencies.
from mne-python.
also see #98
On 10.12.2012, at 20:48, Eric89GXL [email protected] wrote:
Just a reminder to @agramfort to look into notch filtering for 0.6, as our code could easily knock out a small band of frequencies.
—
Reply to this email directly or view it on GitHub.
from mne-python.
@agramfort do you have input on this? I assume you haven't had a chance to look through other packages...
Since I can't work on #11 while traveling, I might try to work on a few options for this: an FIR/FFT band-stop, an IIR band-stop, and I'll try doing what is done in chronux (although I've read through some of that code before, and it's not the easiest thing to understand). Let me know if you have other methods ideas.
from mne-python.
indeed no time to look carefully. I would fly with the code of the standard
toolbox in the domain for inspiration...
from mne-python.
We are using a perl translation of this matlab window-sinc filter,
which does a very nice job for removing power line artifacts from MEG data.
http://www.gomatlab.de/window-sinc-filter-t19156.html
I always wanted to translate it, but always other stuff seemed more
important.
On Fri, Dec 21, 2012 at 9:55 AM, Alexandre Gramfort <
[email protected]> wrote:
indeed no time to look carefully. I would fly with the code of the standard
toolbox in the domain for inspiration...—
Reply to this email directly or view it on GitHubhttps://github.com//issues/98#issuecomment-11606594.
from mne-python.
Closing this to move discussion to #316.
from mne-python.
Related Issues (20)
- `mne.Brain` fails to set renderer when blocking HOT 1
- Add option to import BrainVision files without marker types HOT 5
- BUG: Incompatibility of `sample_weight` with sklearn 1.4+ HOT 2
- BUG: Wrong output for adjacency=False
- bad colormap behavior when brain vlim sliders crossover
- Eyelink: Accept blank recording dates? HOT 3
- Release workflow HOT 16
- The PyQt6 dependency HOT 14
- Logging issue in jupyter kernel when logs are issued in a Thread HOT 4
- Add an SSVEP classification algorithm as a new feature HOT 3
- ValueError: Points have to be provided as one dimensional arrays of length 3. HOT 2
- Request for Sensor Labeling Check in Child-Customized MEG System HOT 2
- Depend on `h5io` and `pymatreader` by default HOT 3
- Tracking issue for (implicit) MNE dependencies still lacking binary wheels for `aarch64` (ARM Linux) HOT 3
- small security upgrade to our upload action
- MAINT: Switch to *_array instead of *_matrix for sparse
- RuntimeWarning for channels with different filter settings on import HOT 12
- Cannot build HTML docs HOT 1
- Export EDF using `mne.export.export_raw`: Signal range error when original data range does not include zero AND data is not equal-length HOT 10
- Add the possibility to provide custom color mapping for channels in raw.plot() HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from mne-python.