FastICA

kizzasi_io

Struct FastICA 

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pub struct FastICA { /* private fields */ }
Expand description

FastICA algorithm for Independent Component Analysis

Separates mixed signals into statistically independent components using higher-order statistics (non-Gaussianity).

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impl FastICA

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pub fn new( n_components: usize, max_iter: Option<usize>, tolerance: Option<f32>, ) -> Self

Create a new FastICA analyzer

§Arguments
  • n_components - Number of independent components to extract
  • max_iter - Maximum iterations (default 200)
  • tolerance - Convergence tolerance (default 1e-4)
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pub fn with_nonlinearity(self, nonlinearity: Nonlinearity) -> Self

Set nonlinearity function

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pub fn fit_transform( &self, mixed: &Array2<f32>, ) -> IoResult<(Array2<f32>, Array2<f32>)>

Fit and transform mixed signals to independent components

§Arguments
  • mixed - Mixed signals (n_samples × n_signals)
§Returns
  • Independent components (n_samples × n_components)
  • Unmixing matrix (n_components × n_signals)

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