Abstract
In this paper, a novel form of the Gaussian filter, the Mittag–Leffler filter is presented. This new filter uses the Mittag–Leffler function in the probability-density function. Such Mittag–Leffler distribution is used in the convolution kernel of the filter. The filter has three parameters that may adjust the curve shape due to the filter-forgetting factor. Illustrative examples present the main advantages of the proposed filter compared to classical Gaussian filtering techniques, as well as real ECG-signal denoising. Some implementation notes, along with the Matlab function, are also presented.
Funder
Slovak Grant Agency for Science
Slovak Research and Development Agency
Army Research Office
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference33 articles.
1. Gaussian Fourier Pyramid for Local Laplacian Filter;IEEE Signal Process. Lett.,2022
2. Functional Bayesian Filter;IEEE Trans. Signal Process.,2022
3. Deng, G., and Cahill, L.W. (November, January 30). An adaptive Gaussian filter for noise reduction and edge detection. Proceedings of the IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference, San Francisco, CA, USA.
4. Chang, K.M., Liu, P.T., and Wei, T.S. (2022). Electromyography Parameter Variations with Electrocardiography Noise. Sensors, 22.
5. Haque, Z., Qureshi, R., Nawaz, M., Khuhawar, F.Y., Tunio, N., and Uzair, M. (2019). Analysis of ECG Signal Processing and Filtering Algorithms. Int. J. Adv. Comput. Sci. Appl., 10.
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