pyFDN.dss_to_tf#

pyFDN.dss_to_tf(delays, A, B, C, D)[source]#

From delay state-space to transfer function matrix (numerator and denominator).

Parameters:
  • delays (array-like) – Delays in samples, shape (N,).

  • A (ndarray) – Feedback matrix, shape (N, N) or (N, N, order) for polynomial matrix.

  • B (array-like) – Input gains, shape (N, num_input).

  • C (array-like) – Output gains, shape (num_output, N).

  • D (array-like) – Direct gains, shape (num_output, num_input).

Return type:

tuple[ndarray, ndarray]

Returns:

  • tfB (ndarray) – Numerator of transfer function matrix, shape (num_output, num_input, order).

  • tfA (ndarray) – Denominator polynomial (common), shape (order,) in z^{-1} convention.