IIR-based pure linear prediction

This paper considers general, pure linear prediction schemes, where the prediction of the input signal is based on IIR-filtered versions of the one-sample-delayed input signal. Properties of these schemes are discussed, in particular, the whitening property and the realization and stability of the s...

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Bibliographic Details
Published in:IEEE transactions on speech and audio processing 2004-01, Vol.12 (1), p.68-75
Main Authors: den Brinker, A.C., Voitishchuk, V., van Eijndhoven, S.J.L.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Finite impulse response filter
Frequency
Information, signal and communications theory
Linear prediction
Mathematical analysis
Mathematics
Nonlinear filters
Optimization
Predictive models
Psychoacoustic models
Signal and communications theory
Signal processing
Signal synthesis
Signal, noise
Simulation
Sound filters
Speech
Stability
Synthesis
Telecommunications and information theory
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Summary:This paper considers general, pure linear prediction schemes, where the prediction of the input signal is based on IIR-filtered versions of the one-sample-delayed input signal. Properties of these schemes are discussed, in particular, the whitening property and the realization and stability of the synthesis filter. In contrast to warped linear prediction, the synthesis filter can be realized in a way similar to the analysis filter. Furthermore, we prove that, at least for a specific class of systems, input data windowing for the calculation of the optimal prediction coefficients guarantees the stability of the synthesis filters. By simulation we show that the proposed prediction scheme, using properly parameterized Laguerre or Kautz systems, shows a behavior similar to that of warped linear prediction.
ISSN:1063-6676
2329-9290
1558-2353
2329-9304
DOI:10.1109/TSA.2003.815524