Levinson-Durbin Algorithm

The Levinson-Durbin Algorithm is a method used in signal processing to efficiently estimate coefficients of an autoregressive (AR) model, which predicts future data points based on past values. It leverages the structure of the autocorrelation matrix—how past values relate to each other—to solve the problem more quickly than standard methods. Think of it as a shortcut to find the best linear prediction of a sequence, making it useful in speech processing, acoustics, and time series analysis. It iterates step-by-step, updating coefficients while minimizing prediction error, resulting in a compact and accurate model.