Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Neurodsp | 260 | 2 | 5 months ago | 13 | September 27, 2022 | 21 | apache-2.0 | Python | ||
Digital signal processing for neural time series. | ||||||||||
Analyzing_neural_time_series | 124 | 3 years ago | mit | Jupyter Notebook | ||||||
python implementations of Analyzing Neural Time Series Textbook | ||||||||||
Dynamicaxiswarping.jl | 89 | 5 months ago | 1 | other | Julia | |||||
Dynamic Time Warping (DTW) and related algorithms in Julia, at Julia speeds | ||||||||||
Matrixprofile.jl | 28 | 6 months ago | 1 | mit | Julia | |||||
Time-series analysis using the Matrix profile in Julia | ||||||||||
8d Audio | 25 | 5 years ago | 2 | Python | ||||||
Some dsp to make songs "8D" | ||||||||||
Pysmooth | 18 | 7 years ago | mit | Python | ||||||
A unique time series library in Python that consists of Kalman filters (discrete, extended, and unscented), online ARIMA, and time difference model. | ||||||||||
Wv | 15 | 8 months ago | 1 | August 30, 2019 | 13 | R | ||||
:alarm_clock: This R package provides the tools to perform standard and robust wavelet variance analysis for time series (signal processing). Among others, aside from computing the wavelet variance and cross-covariance (classic and robust), the package provides inference tools (e.g. confidence intervals) and plotting tools allowing to perform some visual analysis and assess the properties of the underlying time series. | ||||||||||
Computer Vision | 13 | 3 years ago | 2 | Jupyter Notebook | ||||||
Notebook series on interesting topics in computer vision | ||||||||||
Rnn Tutorial | 9 | 6 years ago | mit | Python | ||||||
Signal Processing with Recurrent Neural Networks in TensorFlow | ||||||||||
Anomaly | 6 | 6 years ago | mit | Python | ||||||
This is a non-trivial implementation of anomaly detection in time series as described in ( https://www.ll.mit.edu/mission/cybersec/publications/publication-files/full_papers/2012_08_05_Carter_IEEESSP_FP.pdf ). |