Function File: predictor = dpcmopt (training_set, ord)
Function File: [predictor, partition, codebook] = dpcmopt (training_set, ord, cb)

Optimize the DPCM parameters and codebook.

It uses the Levinson-Durbin algorithm to find the all-pole IIR filter using the autocorrelation sequence. After the best predictor is found, it uses the Lloyds algorithm to find the best codebook and partition for the interval.

predictor = dpcmopt (training_set, ord)

Optimize the DPCM parameters using the Levinson-Durbin algorithm. The predictor vector describes a m-th order prediction for the output according to the following equation y(k) = p(1)sig(k-1) + p(2)sig(k-2) + ... + p(m-1)sig(k-m+1) + p(m)sig(k-m) where the predictor vector is given by predictor = [0, p(1), p(2), p(3),..., p(m-1), p(m)].

training_set is the training data used to find the best predictor.

ord is the order of the desired prediction model.

[predictor, partition, codebook] = dpcmopt (training_set,ord,cb)

Optimize the DPCM parameters and also uses the Lloyds algorithm to find the best codebook and partition for the given training signal.

cb might be the initial codebook used by Lloyds algorithm or the length of the desired codebook.

See also: dpcmenco, dpcmdeco, levinson, lloyds.

Package: communications