A class of adaptive prediction algorithms is considered for model-based digital signal processing. Based on a single adaptive parameter, the so-called general parameter, the algorithm facilitates adaptation of the predictor properties between two boundary cases. Typically, the boundaries are set according to a quick response and good noise attenuation, respectively. The adaptation algorithm is described, two example cases are discussed, and the stability condition is derived.