Adaptive Noise Cancellation Using NLMS Algorithm
This paper studies the behaviour of normalized least mean square (NLMS) adaptive filter algorithm-based noise canceller to eliminate intense background noise of high and low frequency from a desired signal. Noise signal filtration requires a filter which automatically adapts with the variation of input signal and noise signal. Performance is measured by optimizing rate of convergence and mean square error (MSE) using MATLAB. The experimental results indicate that adaptive noise canceller can remove low- and high-frequency noise of signals conveniently, and for small values of step size MSE decreases and for larger value of step size the rate of convergence increases. The computation time increases with the increase of filter length.
KeywordsAdaptive filters LMS algorithm NLMS algorithm Active noise control
This work has been supported by DST-PURSE, Savitribai Phule Pune University. One of the authors R. Rashmi is thankful to the University Grant Commission (UGC) for SRF.
- 3.Haykin, S.: Adaptive Filter Theory, 4th edn. Prentice HallGoogle Scholar
- 4.Mahbub, U., Shahnaz, C., Fattah, S.A.: An adaptive noise cancellation scheme using particle swarm optimization algorithm. In: 2010 International Conference on Communication Control and Computing Technologies (2010)Google Scholar
- 5.Althahab, A.Q.J.: A new robust adaptive algorithm based adaptive filtering for noise cancellation. In: Analog Integrated Circuits and Signal Processing (2017)Google Scholar
- 6.Qiuting, H.: Offset compensation scheme for analogue LMS adaptive fir filters. Electron. Lett. 28(13) (1992)Google Scholar
- 7.Sultana, N., Kamatham, Y., Kinnara, B.: Performance analysis of adaptive filtering algorithms for denoising of ECG signals. In: 2015 International Conference on Advances in Computing Communications and Informatics (ICACCI) (2015)Google Scholar
- 8.Gowri, T., Rajesh Kumar, P., Rama Koti Reddy, D.V.: An efficient variable step size least mean square adaptive algorithm used to enhance the quality of electrocardiogram signal. In: Advances in Intelligent Systems and Computing (2014)Google Scholar
- 9.Shaik, B.S., Naganjaneyulu, G.V.S.S.K.R., Chandrasheker, T., Narasimhadhan, A.V.: A method for QRS delineation based on STFT using adaptive threshold. Procedia Comput. Sci. (2015)Google Scholar
- 11.Dewasthale, M M., Kharadkar, R.D.: Improved NLMS algorithm with fixed step size and filter length using adaptive weight updation for acoustic noise cancellation. In: 2014 Annual IEEE India Conference (INDICON) (2014)Google Scholar