rlevdur#

class diffsptk.ReverseLevinsonDurbin(lpc_order: int)[source]#

See this page for details.

Parameters:

lpc_orderint >= 0: The order of the LPC coefficients, \(M\).

forward(a: Tensor) → Tensor[source]#

Solve a Yule-Walker linear system given the LPC coefficients.

Parameters:

aTensor [shape=(…, M+1)]: The gain and the LPC coefficients.

Returns:

outTensor [shape=(…, M+1)]: The autocorrelation.

Examples

>>> x = diffsptk.nrand(4)
>>> acorr = diffsptk.Autocorrelation(5, 2)
>>> levdur = diffsptk.LevinsonDurbin(2)
>>> rlevdur = diffsptk.ReverseLevinsonDurbin(2)
>>> r = acorr(x)
>>> r
tensor([ 5.8784,  0.8978, -2.0951])
>>> r2 = rlevdur(levdur(r))
>>> r2
tensor([ 5.8784,  0.8978, -2.0951])

diffsptk.functional.rlevdur(a: Tensor) → Tensor[source]#

Solve a Yule-Walker linear system given the LPC coefficients.

Parameters:

aTensor [shape=(…, M+1)]: The gain and the LPC coefficients.

Returns:

outTensor [shape=(…, M+1)]: The autocorrelation.