  A very simple linear signal predictor that uses past predicted values rather
than past signal values for prediction is presented. Man-made or natural
systems utilizing this predictor would not require a memory of input signal
values but only of already predicted, internalized states. This delay-induced
negative group delay (DINGD) predictor affords real-time prediction of signals
without the need for a specific signal model. Its properties are derived
analytically and are numerically tested on various types of broadband input
data.
