LOWPASS IIR PREDICTORS FOR DISCRETE-TIME SIGNAL-PROCESSING

Recently, an optimal prefilter predictor for narrow-band lowpass signa ls was introduced by Laakso and Ovaska. The prefilter predictor consis ts of an application-specific fixed IIR filter cascaded with an analyt ically optimized FIR postfilter. Using this approach, the FIR postfilt er was designed such that polynomial signals of a given order are pred icted to be unchanged, with additional degrees of freedom used for min imization of the noise gain. In this paper, we enhance the original pr efilter approach for more practical filter specifications. Instead of inflexible polynomial constraints and full-band noise power minimizati on, we define an explicit passband and stopband as in conventional fil tering. The new analytical design method enables the flexible control over the frequency domain characteristics of the predictor. Design exa mples are provided to illustrate the indisputable benefits of the new predictor class. (C) 1995 Academic Press, Inc.