Digital Signal Processing for Neural time series
Project description
A package for digital signal processing of neural time series.
Neurodsp contains several modules:
burst : Detect bursting oscillators in neural signals
filt : Filter data with bandpass, highpass, lowpass, or notch filters
laggedcoherence : Estimate rhythmicity using the lagged coherence measure
sim : Simulate bursting or stationary oscillators with brown noise
spectral : Compute spectral domain features (PSD and 1/f slope, etc)
swm : Identify recurrent patterns in a signal using sliding window matching
timefrequency : Estimate instantaneous measures of oscillatory activity
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
neurodsp-2.0.0rc1.tar.gz
(34.4 kB
view hashes)
Built Distribution
Close
Hashes for neurodsp-2.0.0rc1-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 879c9c3d37af3620ae56419c356332aa9a4b1432d1cc9d478c33799a02c7d187 |
|
| MD5 | fc3e89a9673ba26ee1d990d8a7542fa3 |
|
| BLAKE2b-256 | 51bc4929b7ac6aae3892794c57d45ae647c0e0a35d6db4ddf057d216dbbcca3d |
