Efficient linear prediction for digital audio effects
In many audio applications an appropriate spectral estimation from a signal sequence is required. A common approach for this task is the linear prediction  where the signal spectrum is modelled by an all-pole (purely recursive) IIR (infinite impulse response) filter. Linear prediction is commonly used for coding of audio signals leading to linear predictive coding (LPC). But also some audio effects can be created using the spectral estimation of LPC. In this paper we consider the use of LPC in a real-time system. We investigate several methods of calculating the prediction coefficients to have an almost fixed workload each sample. We present modifications of the autocorrelation method and of the Burg algorithm for a sample-based calculation of the filter coefficients as alternative for the gradient adaptive lattice (GAL) method. We discuss the obtained prediction gain when using these methods regarding the required complexity each sample. The desired constant workload leads to a fast update of the spectral model which is of great benefit for both coding and audio effects.