Research Area:  Machine Learning

Abstract:

Non Local Mean (NLM) filter has attracted great attention within the images and signal processing field especially in the last ten years. The main contribution of this paper to the field of biomedical signals processing is introducing the straightforward application of the fast NLM filter to EEG signal contaminated with "Additive White Gaussian Noise" (AWGN). The performance of this filter is analysed by evaluating its optimal parameters. All the tests are conducted using actual EEG signal captured from human brain. The performance of this filter is determined using "Output Signal to Noise Ratio" (SNRo) and "Cross Correlation" (CC) criteria. The NLM filter exhibits excellent performance in rejection the AWGN from the EEG signal.

Keywords:  
Eeg Signal
Non Local Mean Approach
Additive White Gaussian Noise
Output Signal to Noise Ratio
Cross Correlation
biomedical signals
Machine Learning
Deep Learning

Author(s) Name:  Anas Fouad Ahmed

Publisher name:  Journal of Al-Rafidain University College For Sciences

DOI:  10.55562/jrucs.v41i3.189

Volume Information:   No. 3 (2017): 2017 Volume , Issue 41

Paper Link:   http://jrucs.iq/index.php/JAUCS/article/view/189