Abstract
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.
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Acknowledgements
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.
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Rashmi, R., Jagtap, S. (2019). Adaptive Noise Cancellation Using NLMS Algorithm. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_53
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DOI: https://doi.org/10.1007/978-981-13-3393-4_53
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