SpKit: Signal Processing ToolKit
Project description
Signal Processing toolkit
Links: Homepage | Documentation | Github | PyPi - project | _ Installation: pip install spkit
Installation
Requirement: numpy, matplotlib, scipy.stats, scikit-learn, seaborn
with pip
pip install spkit
update with pip
pip install spkit --upgrade
New in 0.0.9.5:
MEA Processing Toolkit
- sp.mea
Geometrical Functions
- sp.gemetry
More on signal processing
- sp.core
Statistics
- sp.stats
For updated list of contents and documentation check github or Documentation
List of all functions
Signal Processing Techniques
Information Theory functions
for real valued signals
-
Entropy
- Shannon entropy
- Rényi entropy of order α, Collision entropy,
- Joint entropy
- Conditional entropy
- Mutual Information
- Cross entropy
- Kullback–Leibler divergence
- Spectral Entropy
- Approximate Entropy
- Sample Entropy
- Permutation Entropy
- SVD Entropy
-
Plot histogram with optimal bin size
-
Computation of optimal bin size for histogram using FD-rule
-
Compute bin_width with various statistical measures
-
Plot Venn Diagram- joint distribuation and normalized entropy values
Dispersion Entropy --for time series (physiological signals)
- Dispersion Entropy (Advanced) - for time series signal
- Dispersion Entropy
- Dispersion Entropy - multiscale
- Dispersion Entropy - multiscale - refined
Matrix Decomposition
- SVD
- ICA using InfoMax, Extended-InfoMax, FastICA & Picard
Continuase Wavelet Transform
- Gauss wavelet
- Morlet wavelet
- Gabor wavelet
- Poisson wavelet
- Maxican wavelet
- Shannon wavelet
Discrete Wavelet Transform
- Wavelet filtering
- Wavelet Packet Analysis and Filtering
Basic Filtering
- Removing DC/ Smoothing for multi-channel signals
- Bandpass/Lowpass/Highpass/Bandreject filtering for multi-channel signals
Biomedical Signal Processing
MEA Processing Toolkit
Artifact Removal Algorithm
- ATAR Algorithm Automatic and Tunable Artifact Removal Algorithm for EEG from artical
- ICA based Algorith
Analysis and Synthesis Models
- DFT Analysis & Synthesis
- STFT Analysis & Synthesis
- Sinasodal Model - Analysis & Synthesis
- to decompose a signal into sinasodal wave tracks
- f0 detection
Ramanajum Methods for period estimation
- Period estimation for a short length sequence using Ramanujam Filters Banks (RFB)
- Minizing sparsity of periods
Fractional Fourier Transform
- Fractional Fourier Transform
- Fast Fractional Fourier Transform
Machine Learning models - with visualizations
- Logistic Regression
- Naive Bayes
- Decision Trees
- DeepNet (to be updated)
Linear Feedback Shift Register
- pylfsr
Cite As
@software{nikesh_bajaj_2021_4710694,
author = {Nikesh Bajaj},
title = {Nikeshbajaj/spkit: 0.0.9.4},
month = apr,
year = 2022,
publisher = {Zenodo},
version = {0.0.9.4},
doi = {10.5281/zenodo.4710694},
url = {https://doi.org/10.5281/zenodo.4710694}
}
Contacts:
- Nikesh Bajaj
- http://nikeshbajaj.in
- n.bajaj[AT]qmul.ac.uk, n.bajaj[AT]imperial[dot]ac[dot]uk
Imperial College London
Project details
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