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alphacsc 0.4.1 documentation

  • Model descriptions
  • Examples Gallery
  • API Documentation
  • GitHub
  • PyPI
  • Model descriptions
  • Examples Gallery
  • API Documentation
  • GitHub
  • PyPI

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  • Univariate CSC
    • Selecting random state for CSC
    • CSC to learn LFP spiking atoms
    • Extracting cross-frequency coupling waveforms from rodent LFP data
    • Vanilla CSC on simulated data
  • Univariate and Multivariate CSC with ‘dicodile’ solver
    • Gait (steps) example
  • Multivariate CSC with rank 1 constraints
    • Extracting \(\mu\)-wave from the somato-sensory dataset
    • Extracting artifact and evoked response atoms from the MNE sample dataset
    • Extracting artifact and evoked response atoms from the sample dataset
  • Univariate CSC with an alpha-stable distribution
    • Alpha CSC on simulated data
    • Alpha CSC on empirical time-series with strong artifacts
  • Other shift-invariant dictionary learning algorithms
    • MoTIF on simulated data
    • SWM on simulated data
  • Examples Gallery
  • Multivariate CSC with rank 1 constraints

Multivariate CSC with rank 1 constraints#

Extracting \mu-wave from the somato-sensory dataset

Extracting \mu-wave from the somato-sensory dataset

Extracting artifact and evoked response atoms from the MNE sample dataset

Extracting artifact and evoked response atoms from the MNE sample dataset

Extracting artifact and evoked response atoms from the sample dataset

Extracting artifact and evoked response atoms from the sample dataset

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Gait (steps) example

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Extracting \(\mu\)-wave from the somato-sensory dataset

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