lpc
Contents
lpc
Compute the linear prediction coefficients using a Hamming window.
Usage:
lpc(x, m, p {, out, lfft})
Function:
Computes the linear prediction coefficients or the lpc smoothed spectrum of the signal vector x using the auto-correlation method.
Parameters:
- x
- An unwindowed signal vector.
- m
- The number of coefficients.
- p
- The pre-emphasis factor (
0 <=
p<= 1
).
- out
- The output selector. See the result for details.
- lfft
- The fft length for smoothed spectrum.
Result:
A vector y
. The type of vector depends on the parameter out:
0
- A smoothed linear amplitude spectrum where length =
lfft/2+1
and y[0 ..
lfft/2]
.
1
- The error energy and inverse filter coefficients where length =
m+2
and y[0] = alpha
and y[1 ..
m+1] = AI[0..
m]
.
2
- The error energy and reflection coefficients where length =
m+1
, y[0] = alpha
and y[1..
m] = RC[0..
m-1]
.
3
- The error energy and area coefficients where length =
m+1
, y[0] = alpha
and y[1..
m] = AR[0..
m-1]
.
4
- The error energy and log. area coefficients where length =
m+1
, y[0] = alpha
and y[1..
m] = sqrt(AR[0..
m-1])
.