tf.spectral.idct

tf.spectral.idct(
input,
type=2,
n=None,
axis=-1,
norm=None,
name=None
)


See the guide: Spectral Functions > Discrete Cosine Transforms

Computes the 1D Inverse Discrete Cosine Transform (DCT) of input.

Currently only Types II and III are supported. Type III is the inverse of Type II, and vice versa.

Note that you must re-normalize by 1/(2n) to obtain an inverse if norm is not 'ortho'. That is: signal == idct(dct(signal)) * 0.5 / signal.shape[-1]. When norm='ortho', we have: signal == idct(dct(signal, norm='ortho'), norm='ortho').

Args:

• input: A [..., samples] float32 Tensor containing the signals to take the DCT of.
• type: The IDCT type to perform. Must be 2 or 3.
• n: For future expansion. The length of the transform. Must be None.
• axis: For future expansion. The axis to compute the DCT along. Must be -1.
• norm: The normalization to apply. None for no normalization or 'ortho' for orthonormal normalization.
• name: An optional name for the operation.

Returns:

A [..., samples] float32 Tensor containing the IDCT of input.

Raises:

• ValueError: If type is not 2 or 3, n is not None,axisis not-1, ornormis notNoneor'ortho'`.

Scipy Compatibility

Equivalent to scipy.fftpack.idct for Type-II and Type-III DCT. https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.fftpack.idct.html