spkit
  • Site

      Getting started

      • Installation
      • Links:
      • Customisation

      Information Theory

      • Information Theory for Real-Valued signals
      • Dispersion Entropy

      EEG Artifact Removal Algorithms

      • ATAR - Automatic and Tunable Artifact Removal Algorithm for EEG
      • Blind Source Seperation - ICA Based Artifact Removal

      EEG Topographic Maps (Spatio-Temporal/Spectral)

      • EEG Topographic Maps
      • Multi-Electrode Arrays Processing
      • 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
      • Independent Component Analysis - ICA
      • Machine Learning
      • Periodogram
      • A quick stats of an array
      • Compute statistical outliers
      • Link to pylfsr documentation
      • API docs
      • ChangeLog
      • Contacts
  • Page
      • Link to pylfsr documentation
        • Example: 5 bit LFSR with x^5 + x^2 + 1
        • Check out full documentation of LFSR**
  • « Periodogram
  • API docs »
  • Source

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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© Copyright 2019, Nikesh Bajaj.
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