Closed form expressions for optimum FIR polynomial predictive filtering

Emmanouil Z. Psarakis; George V. Moustakides

Closed form expressions for optimum FIR polynomial predictive filtering

Emmanouil Z. Psarakis, George V. Moustakides

Research output: Contribution to journal › Conference article › peer-review

Abstract

We propose two different approaches for finding optimum FIR polynomial predictive filters. The first reveals an important property of these filters and can lead to a numerical solution that is of the size of the number of constraints imposed instead of the size of the filter. With the second method, using a different parametrization of the filter coefficients, it is possible to obtain closed form expressions for the optimum filter coefficients and for the minimum output noise power, in the general case. Previous approaches were successful in providing closed forms expressions only for special cases.

Original language	English (US)
Article number	7071865
Journal	European Signal Processing Conference
Volume	2002-March
State	Published - Mar 27 2002
Externally published	Yes
Event	11th European Signal Processing Conference, EUSIPCO 2002 - Toulouse, France Duration: Sep 3 2002 → Sep 6 2002

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

Cite this

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AU - Psarakis, Emmanouil Z.

AU - Moustakides, George V.

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N2 - We propose two different approaches for finding optimum FIR polynomial predictive filters. The first reveals an important property of these filters and can lead to a numerical solution that is of the size of the number of constraints imposed instead of the size of the filter. With the second method, using a different parametrization of the filter coefficients, it is possible to obtain closed form expressions for the optimum filter coefficients and for the minimum output noise power, in the general case. Previous approaches were successful in providing closed forms expressions only for special cases.

AB - We propose two different approaches for finding optimum FIR polynomial predictive filters. The first reveals an important property of these filters and can lead to a numerical solution that is of the size of the number of constraints imposed instead of the size of the filter. With the second method, using a different parametrization of the filter coefficients, it is possible to obtain closed form expressions for the optimum filter coefficients and for the minimum output noise power, in the general case. Previous approaches were successful in providing closed forms expressions only for special cases.

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M3 - Conference article

AN - SCOPUS:84960877833

SN - 2219-5491

VL - 2002-March

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M1 - 7071865

T2 - 11th European Signal Processing Conference, EUSIPCO 2002

Y2 - 3 September 2002 through 6 September 2002

ER -

Closed form expressions for optimum FIR polynomial predictive filtering

Abstract

All Science Journal Classification (ASJC) codes

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