lpccheck

class diffsptk.LinearPredictiveCoefficientsStabilityCheck(lpc_order: int, margin: float = 1e-16, warn_type: str = 'warn')

See this page for details.

Parameters:

lpc_orderint >= 0

The order of the LPC, \(M\).

marginfloat in (0, 1)

The margin to guarantee the stability of LPC.

warn_type[‘ignore’, ‘warn’, ‘exit’]

The warning type.

forward(a: Tensor) → Tensor

Check the stability of the input LPC coefficients.

Parameters:

aTensor [shape=(…, M+1)]

The input LPC coefficients.

Returns:

outTensor [shape=(…, M+1)]

The modified LPC coefficients.

Examples

>>> x = diffsptk.nrand(4)
tensor([-0.9966, -0.2970, -0.2173,  0.0594,  0.5831])
>>> lpc = diffsptk.LPC(3, 5)
>>> a = lpc(x)
>>> a
tensor([ 1.1528, -0.2613, -0.0274,  0.1778])
>>> lpccheck = diffsptk.LinearPredictiveCoefficientsStabilityCheck(3)
>>> a2 = lpccheck(a)
tensor([ 1.1528, -0.2613, -0.0274,  0.1778])

diffsptk.functional.lpccheck(a: Tensor, margin: float = 1e-16, warn_type: str = 'warn') → Tensor

Check stability of LPC coefficients.

Parameters:

aTensor [shape=(…, M+1)]

The input LPC coefficients.

marginfloat in (0, 1)

The margin to guarantee the stability of LPC.

warn_type[‘ignore’, ‘warn’, ‘exit’]

The warning type.

Returns:

outTensor [shape=(…, M+1)]

The modified LPC coefficients.

See also

lpc lpc2par par2lpc