Frequency and time constrained digital filter design

• Autorzy: Henzel N.
• Języki publikacji: EN

Abstrakty

EN

This paper describes a new method for linear phase finite impulse response (FIR) filters design. This new approach, based on the ε-insensitive loss function, allows the design process to take into account not only constraints specified in the frequency domain, but also constraints on the output, time domain, signal. The performances of the proposed approach are shortly illustrated by a high-pass filter for ECG baseline wander reduction.

Słowa kluczowe

EN

digital filter design; biomedical signal noise reduction; ε-insensitive loss function

PL

projektowanie filtrów cyfrowych; redukcja szumów sygnału biomedycznego; ε-nieczuła funkcja straty

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2006
• Tom: Vol. 10
• Strony: 103--112
• Opis fizyczny: Bibliogr. 12 poz., fig.

Twórcy

autor

Henzel N.

• Silesian University of Technology, Institute of Electronics, Akademicka 16, 44-101 Gliwice, Poland

Bibliografia

• [1] CANAN S., OZBAY Y., KARLIK B., A Method for Removing Low Frequency Trend From ECG Signal, Proc. of Int. Conf. Biomed. Engin. Days, pp.144−146, 1998.
• [2] CIARLINI P., BARONE P., A Recursive Algorithm to Compute the Baseline Drift in Recorded Biological Signals, Compt. Biomed. Res., Vol. 21, pp. 221–226, 1988.
• [3] FRANKIEWICZ Z., Methods for ECG signal analysis in the presence of noise, Ph.D. Thesis, Silesian Technical University, Gliwice, 1987.
• [4] HENZEL N., Constrained design of digital FIR filters, Computer Recognition Systems - KOSYR 2003, Wrocław, pp. 457−462, 2003.
• [5] ŁĘSKI J., HENZEL N., An ε-insensitive learning in neuro-fuzzy modelling, Proceedings of VI Conference Neural Networks and Soft Computing, Zakopane, pp. 531–536, 2002.
• [6] ŁĘSKI J., Towards a robust fuzzy clustering. Fuzzy Sets and Systems, Vol. 137, pp. 215–233, 2003.
• [7] ŁĘSKI, HENZEL N., ECG baseline wander and powerline interference reduction using nonlinear filter bank, Signal Processing Vol. 85,pp. 781–793, 2005.
• [8] McCLELLAN J., PARKS T., A united approach to the design of optimum FIR linear-phase digital filters. IEEE Transactions on Circuits and Systems, Vol. 20, No. 6, pp. 697–701, 1973.
• [9] RICCIO M. L., BELINA J. C., A Versatile Design method of Fast, Linear-Phase FIR Filtering Systems for Electrocardiogram Acquisition and Analysis Systems, Proc. of Int. Conf. Comput. Cardiol., pp.147–150, 1992.
• [10] SCHÖLKOPF B. et al., Comparing support vector machines with Gaussian kernels to radial basis function classifiers, IEEE Trans. Sign. Processing, Vol. 45, pp. 2758–2765, 1997.
• [11] VAPNIK V., Statistical Learning Theory. Wiley, New York, 1998.
• [12] VAN ALSTE J. A., VAN ECK W., HERRMANN O.E., ECG Baseline Wander Reduction Using Linear Phase Filters, Compt. Biomed. Res., Vol. 19, pp. 417–427, 1986.