tf.signal.dct
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.
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Last updated 2020-10-01 UTC.
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