This lecture covers the estimation and linear prediction of past values in signal processing, focusing on prediction coefficients and the minimization of the mean squared error. It also discusses the relationship between prediction filters and white noise generation, as well as the Levinson-Durbin algorithm for finding solutions to normal equations.