NOISE CANCELLATION WITH LMS VARIANTS

Year 2021, Volume: 26 Issue: 1, 153 - 170, 30.04.2021

Fahri Vatansever

https://doi.org/10.17482/uumfd.797087

Cited By: 2

Abstract

The noise is one of the important factors that affect negatively the operation of circuits and systems. There are different methods and techniques for cancelling/reducing/de-noising these unwanted signals that mix with the original signal. In this study, an application/simulator that performs noise cancellation operations with least mean-squares algorithms was designed. The application, which has powerful visual support and a user-friendly interactive interface, can make single or comparative noise cancellation operations and performance analyzes with different algorithms on noisy signals. The effects of the algorithm parameters can be observed, information about the related algorithms can be obtained via the developed application that can also be used for educational purpose.

Keywords

Noise cancellation, LMS, adaptive filter, simulator

LMS Varyantlarıyla Gürültü Arındırma

Abstract

Devre ve sistemlerin işleyişlerini olumsuz yönde etkileyen önemli faktörlerden birisi de gürültülerdir. Orijinal işarete karışan bu istenmeyen işaretlerin arındırılması/azaltılması/temizlenmesi için farklı yöntem ve teknikler mevcuttur. Gerçekleştirilen çalışmada, en küçük karesel ortalama algoritmalarıyla gürültü arındırma işlemlerini gerçekleştiren bir uygulama/simülatör tasarlanmıştır. Güçlü görsel desteğe ve kullanıcı dostu etkileşimli arayüze sahip, eğitim amaçlı da kullanılabilen uygulama ile gürültülü işaretler üzerinde, farklı algoritmalarla tekli veya karşılaştırmaları gürültü arındırma işlemleri ve performans analizleri yapılabilmekte, algoritma parametrelerinin etkileri gözlemlenebilmekte ve ilgili algoritmalar hakkında bilgiler edinilebilmektedir.

Keywords

Gürültü arındırma, LMS, adaptif filtre, simülatör

References

• Bismor, D., Czyz, K., Ogonowski, Z. (2016) Review and comparison of variable step-size LMS algorithms, The International Journal of Acoustics and Vibration, 21, 24-39. doi: https://doi.org/10.20855/ijav.2016.21.1392.
• Diniz, P.S.R. (2020) Adaptive Filtering: Algorithms and Practical Implementation, 5th ed., Springer, Switzerland.
• Dixit, S., Nagaria, D. (2017) LMS adaptive filters for noise cancellation: A review, International Journal of Electrical and Computer Engineering, 7(5), 2520-2529. doi: https://doi.org/10.11591/ijece.v7i5.pp2520-2529
• Farhang-Boroujeny, B. (2013) Adaptive Filters: Theory and Applications, 2nd ed., Wiley.
• Goel, P., Chandra, M. (2019) FPGA implementation of adaptive filtering algorithms for noise cancellation - A Technical survey, In: Nath, V., Mandal, J. (eds) Proceedings of the Third International Conference on Microelectronics, Computing and Communication Systems. Lecture Notes in Electrical Engineering, 556, Springer, Singapore. https://doi.org/10.1007/978-981-13-7091-5_42.
• Gorriz, J.M, Ramirez, J., Cruces-Alvarez, S., Puntonet, C.G., Lang, E.W., Erdogmus, D. (2009) A Novel LMS algorithm applied to adaptive noise cancellation, IEEE Signal Processing Letters, 16(1), 34-37. doi: https://doi.org/10.1109/LSP.2008.2008584.
• Guda, M., Gasser, S., El Mahallawy, M.S. (2014) MATLAB simulation comparison for different adaptive noise cancelation algorithms, The International Conference on Digital Information, Networking, and Wireless Communications (DINWC), Czech Republic, 68-73.
• Hatun, M., Vatansever, F. (2016) Differential equation solver simulator for Runge-Kutta methods, Uludağ University Journal of The Faculty of Engineering, 21(1), 147-164. doi: https://doi.org/10.17482/uujfe.70981.
• Haykin, S. (2014) Adaptive Filter Theory, 5th ed., Pearson, USA.
• Kaçar, S., Çankaya, İ. (2010) Volterra serileri metodu ile doğrusal olmayan sistemlerin frekans boyutunda analizi için .NET tabanlı arayüz tasarımı, Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi, 12(3), 87-102.
• Kaçar, S., Çankaya, İ. (2012) MATLAB ve ASP.NET tabanlı web arayüzü kullanılarak doğrusal olmayan sistemlerin analizi, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 27(4), 795-806.
• Kaçar, S., Boz, A.F., Arıcıoğlu, B., Tekin, H. (2017) PID denetleyici uygulamaları için yeni bir online deney seti tasarımı, Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(1), 34-46. doi: https://doi.org/10.16984/saufenbilder.284220.
• Lee, J-H., Ooi, L-E., Ko, Y-H., Teoh, C-Y. (2017) Simulation for noise cancellation using LMS adaptive filter, IOP Conf. Series: Materials Science and Engineering, 211, 012003, doi: https://doi.org/10.1088/1757-899X/211/1/012003.
• Maddala, S. (2010) A simulator for depicting and comparing adaptive algorithms in signal processing, 2010 International Conference on Signal and Image Processing, Chennai, 515-520. doi: https://doi.org/10.1109/ICSIP.2010.5697530.
• Maurya, A.K. (2018) Cascade–cascade least mean square (LMS) adaptive noise cancellation, Circuits Syst Signal Process, 37, 3785–3826. doi: https://doi.org/10.1007/s00034-017-0731-2.
• Maurya, A.K., Agrawal, P., Dixit, S. (2019) Modified model and algorithm of LMS adaptive filer for noise cancellation, Circuits Syst Signal Process, 38, 2351-2368. doi: https://doi.org/10.1007/s00034-018-0952-z.
• Morales, L.G. (Ed.) (2011) Adaptive Filtering Applications, InTech, Croatia.
• Poularikas, A.D. (2015) Adaptive Filtering, CRC Press.
• Romero, I., Geng, D., Berset, T. (2012) Adaptive filtering in ECG denoising: A comparative study, 2012 Computing in Cardiology, Krakow, 45-48.
• Qureshi, R., Rizvi, S.A.R., Musavi, S.H.A., Khan, S., Khurshid, K. (2017) Performance analysis of adaptive algorithms for removal of low frequency noise from ECG signal, 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT), Karachi, 1-5. doi: https://doi.org/10.1109/ICIEECT.2017.7916551.
• Sankar, A.B., Kumar, D., Seethalakshmi, K. (2010) Performance study of various adaptive filter algorithms for noise cancellation in respiratory signals, Signal Processing: An International Journal (SPIJ), 4(5), 267-278.
• Sayed, A.H. (2008) Adaptive Filters, Wiley, USA.
• Taha, T.M.F., Adeel, A., Hussain, A. (2018) A Survey on techniques for enhancing speech, International Journal of Computer Applications, 179(17), 1-14. doi: https://doi.org/10.5120/ijca2018916290.
• Thakor, N.V., Zhu, Y-S. (1991) Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection, IEEE Transactions on Biomedical Engineering, 38(8), 785-794. doi: https://doi.org/10.1109/10.83591.
• The MathWorks Inc. (2018) MATLAB , App Designer.
• Vatansever, F., Yalcin, N.A. (2017) e-Signals & Systems: A web-based educational tool for signals and systems, Computer Applications in Engineering Education, 25(4), 625-641. doi: https://doi.org/10.1002/cae.21826.
• Vatansever, F., Hatun, M. (2019) The system stability software tool based on Routh-Hurwitz criterion, Uludağ University Journal of The Faculty of Engineering, 24(2), 229-238. doi: https://doi.org/10.17482/uumfd.545361.
• Yalcin, N.A., Vatansever, F. (2016) A Web-based virtual power electronics laboratory, Comput. Appl. Eng. Educ., 24(1), 71-78. doi: https://doi.org/10.1002/cae.21673.
• Widrow, B., Glover, J.R., McCool, J.M., Kaunitz, J., Williams, C.S., Hearn, R.H., Zeidler, J.R., Donc, E., Goodlin, R.C. (1975) Adaptive noise cancelling: Principles and applications, Proceedings of the IEEE, 63(12), 1692-1716. doi: https://doi.org/10.1109/PROC.1975.10036.
• Widrow, B., Stearns, S.D. (1985) Adaptive Signal Processing, Prentice-Hall, USA.
• Zaknich, A. (2005) Principles of Adaptive Filters and Self-learning Systems, Springer, Germany.