dolpc: (Perceptive) Linear Prediction

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/dolpc.R

Description

Compute autoregressive model from spectral magnitude samples via Levinson-Durbin recursion.

Usage

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dolpc(x, modelorder = 8)

Arguments

x

Matrix of spectral magnitude samples (each sample/time frame in one column).

modelorder

Lag of the AR model.

Value

Returns a matrix of the normalized AR coefficients (depending on the input spectrum: LPC or PLP coefficients). Every column represents one time frame.

Author(s)

Sebastian Krey [email protected]

References

Daniel P. W. Ellis: http://www.ee.columbia.edu/~dpwe/resources/matlab/rastamat/

See Also

levinson

Examples

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  testsound <- normalize(sine(400) + sine(1000) + square(250), "16")
  pspectrum <- powspec(testsound@left, testsound@samp.rate)
  aspectrum <- audspec(pspectrum, testsound@samp.rate)$aspectrum
  lpcas <- dolpc(aspectrum, 10)

tuneR documentation built on July 10, 2018, 1:02 a.m.