Denoising ECG Signals by Using Extended Kalman Filter to Train Multi-Layer Perceptron Neural Network-Reference-Cited by-同舟云学术

Denoising ECG Signals by Using Extended Kalman Filter to Train Multi-Layer Perceptron Neural Network

Published:2018-11 Issue:6 Volume:52 Page:528-538
ISSN:0146-4116
Container-title:Automatic Control and Computer Sciences
language:en
Short-container-title:Aut. Control Comp. Sci.

Author:

Gaamouri S.,Salah M. Bousbia,Hamdi R.

Publisher

Allerton Press

Subject

Signal Processing,Control and Systems Engineering,Software

Link

http://link.springer.com/article/10.3103/S0146411618060044/fulltext.html

Reference30 articles.

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3. Kaur, T., A review for removal of baseline wander noise in ECG using various techniques, Int. J. Res. Appl. Sci. Eng. Technol., 2015, vol. 3, no. 7, pp. 2321–9653.

4. Gotchev, A., Nikolaev, N. and Egiazaian, K., Improving the transform domain ECG denoising performance by applying inter beat and intra-beat decorrelating transforms, Proc. The 2001 IEEE International Symposium on Circuits and Systems, 2001, pp. 17–20.

5. Karthika, R., Narender, K., Tech, M., and Vikram, B.R., ECG signal denoising using least-mean-square and normalised-least-mean-square algorithm based adaptive filter, Int. J. Mag. Eng., 2015, vol. 2, no. 2015, pp. 640–646.

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