tf.signal.dct

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

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

Currently only Types I, II and III are supported. Type I is implemented using a length 2N padded tf.signal.rfft. Type II is implemented using a length 2N padded tf.signal.rfft, as described here: Type 2 DCT using 2N FFT padded (Makhoul). Type III is a fairly straightforward inverse of Type II (i.e. using a length 2N padded tf.signal.irfft).

Args:

• input: A [..., samples] float32/float64 Tensor containing the signals to take the DCT of.
• type: The DCT type to perform. Must be 1, 2 or 3.
• n: The length of the transform. If length is less than sequence length, only the first n elements of the sequence are considered for the DCT. If n is greater than the sequence length, zeros are padded and then the DCT is computed as usual.
• 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/float64 Tensor containing the DCT of input.

Raises:

• ValueError: If type is not 1, 2 or 3, axis is not -1, n is not None or greater than 0, or norm is not None or 'ortho'.
• ValueError: If type is 1 and norm is ortho.

Scipy Compatibility

Equivalent to scipy.fftpack.dct for Type-I, Type-II and Type-III DCT.