Hi, I'm researching lossless compression for a highschool mathematics research essay and am fairly confused about how the linear prediction coefficients are solved for within flac.
As far as I understand, Levinson Durbin Recursion is used to solve for these coefficients, however, what I don't understand is what the toeplitz matrix is composed of. I found sources using samples from within the time series to construct a linear system: http://practicalcryptography.com/miscellaneous/machine-learning/linear-prediction-tutorial/ However, talkbox, a scikit for signal proccessing ( https://github.com/cournape/talkbox/tree/master/scikits/talkbox/linpred ), first autocorrolates the signal using discrete inverse Fourier transforms which then passes it to the levinson durbin algorithm. I would really appriciate an explanation or information on a good resource to learn more about how the prediction coefficients are solved for. Once the lpc coefficients have been solved, as far as I understand you must also store part of original signal with length equal to the prediction order since you need the previous samples to predict the next sample of which only the residual is known. For the next values the residual is used to retrieve the original value which is fed into the predction model to further reconstruct the time series. Is this correct? Kind Regards, Robin Decker _______________________________________________ flac-dev mailing list flac-dev@xiph.org http://lists.xiph.org/mailman/listinfo/flac-dev
