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Polynomial Predictive Filters (PPFs) are capable of predicting future values of a signal that can be modeled as a polynomial of a low degree. FIR PPFs succeed at predicting the signal, but suffer from poor stopband attenuation and exhibit a disturbing passband gain peak. The introduction of feedback terms to the basic FIR structure effectively remedies these problems, but no well-developed method...
We present an efficient method of designing polynomial predictive IIR filters via feedback extension of FIR predictive filters. The advantage of the IIR structures over their FIR counterparts is a more desirable frequency response obtained with considerably smaller memory and computational overhead. In this paper, we show that the IIR structure is able to predict complex-valued signals as well....
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