Adaptive IIR filter based on penalized spline

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The purpose of this research is to develop the technique of spline adaptive filters (SAF) for real-time implementation. The P-SAF proposed in the article based on the recurrent penalty P-spline, by analogy with the classical SAF, consists of linear dynamic and nonlinear static components. To adapt P-SAF, computing circuits with different topologies have been developed. This approach specifies a way to adapt the knots and calculate the spline coefficients simultaneously. This made it possible to increase the efficiency of P-SAF compared to the classical SAF and reduce computational costs. The efficiency indicator MSE [dB] for P-SAF is equal to and higher than for classical SAF when analyzing model and real time series.

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作者简介

E. Kochegurova

National Research Tomsk Polytechnic University

编辑信件的主要联系方式.
Email: kocheg@mail.ru
俄罗斯联邦, Lenina Prospekt 30, Tomsk, 634050

I. Martynova

National Research Tomsk Polytechnic University

Email: martynova@tpu.ru
俄罗斯联邦, Lenina Prospekt 30, Tomsk, 634050

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2. Fig. 1. Structure of the spline adaptive filter.

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3. Fig. 2. Topology of R-SAF computing circuits.

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4. Fig. 3. Structural diagram of the recurrent P-SAF.

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5. Fig. 4. P-SAF stability regions.

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6. Rice. 5. Hardware function P-SAF.

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7. Fig. 6. Efficiency of the P-SAF algorithm under Gaussian random process conditions.

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8. Fig. 7. Efficiency of the P-SAF algorithm for the Doppler function.

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9. Fig. 8. Performance of the P-SAF algorithm for dataset No. 96-008 DaISy.

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10. Fig. 9. Performance of the P-SAF algorithm for dataset No. 96-004 DaISy.

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