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Probabilistic Error Free Design of Long Fixed-Point Polynomial FIR Predictors

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3 Author(s)
Jarno M. A. Tanskanen ; Tampere University of Technology, Ragnar Granit Institute, P.O. Box 692, FI-33101 Tampere, FINLAND. Tel. +358 3 3116 4016, +358 50 3871 347, Fax: +358 3 3116 4013, E-mail: tanskanen@ieee.org ; Jari A. K. Hyttinen ; Vassil S. Dimitrov

In this paper, a method for designing long fixed-point polynomial FIR predictors (FPFPs) is proposed. Our method yields filters that perform exact prediction even with short coefficient word lengths. Under ordinary coefficient quantization, prediction capabilities degrade, or may be totally lost. Here, the filters are designed so that the prediction properties are exactly preserved in fixed-point implementations. The algorithm is derived for second degree polynomial prediction using any filter length and integer prediction step. Also some non-integer prediction steps are possible

Published in:

Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006

Date of Conference:

7-9 June 2006