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SpKit: Signal Processing ToolKit

Project description

Signal Processing toolkit

Links: Homepage | Documentation | Github | PyPi - project | _ Installation: pip install spkit


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Installation

Requirement: numpy, matplotlib, scipy.stats, scikit-learn, seaborn

with pip

pip install spkit

update with pip

pip install spkit --upgrade

New in 0.0.9.7:

MEA Processing Toolkit

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

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:

Imperial College London


Project details


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