Abstract
In this chapter, fundamentals of adaptive filter are explained. Application of adaptive filter over EEG and ECG signals has been demonstrated and explained clearly in a simple way. All the implementation details of LMS and NLMS algorithms for adaptive filter are also provided along with MatLab codes. This chapter provides a complete study of noise cancellation of EEG and ECG signals. These studies include dataset description, details about noise signal, and modeling of problem as adaptive noise canceller model. Proper visualization of signal before and after the filtering process is given with values of different fidelity parameters used to check the quality of filtered signals. MatLab code for the complete study is also provided to give the real experience of entire process. Famous EEG and ECG datasets, which are publicly accessible, are used. With the input of this chapter, any reader can easily implement and use adaptive filters for filtering of any biomedical signals.
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Ahirwal, M.K., Kumar, A., Singh, G.K. (2021). Fundamentals of Adaptive Filters. In: Computational Intelligence and Biomedical Signal Processing. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-67098-6_2
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DOI: https://doi.org/10.1007/978-3-030-67098-6_2
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