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  • Links:
  • Installation
  • Information Theory for Real-Valued signals
  • Dispersion Entropy
  • ATAR - Automatic and Tunable Artifact Removal Algorithm for EEG
  • Blind Source Seperation - ICA Based Artifact Removal
  • Complex Wavelets
  • Ramanujan Filter Banks
  • Analysis and Synthesis Models
  • DFT: Analysis and Synthesis
  • STFT: Analysis and Synthesis
  • FRFT: Fractional Fourier Transform
  • Sinasodal Model: Analysis and Synthesis
  • Fractional Fourier Transform
  • Signal Filtering
  • Wavelet Filtering
  • Independent Component Analysis - ICA
  • EEG Topographic Maps
  • Machine Learning
  • Periodogram
  • A quick stats of an array
  • Compute statistical outliers
  • Link to pylfsr documentation
    • Example: 5 bit LFSR with x^5 + x^2 + 1
    • Check out full documentation of LFSR**
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  • Docs »
  • Link to pylfsr documentation
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Link to pylfsr documentation¶

Example: 5 bit LFSR with x^5 + x^2 + 1¶

import numpy as np
from spkit.pylfsr import LFSR

L = LFSR()
L.info()
L.next()
L.runKCycle(10)
L.runFullCycle()
L.info()
tempseq = L.runKCycle(10000)    # generate 10000 bits from current state

Check out full documentation of LFSR**¶

https://lfsr.readthedocs.io/

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