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Image Search Results
Journal: IEEE Journal of Translational Engineering in Health and Medicine
Article Title: Comparative Study of Wavelet-Based Unsupervised Ocular Artifact Removal Techniques for Single-Channel EEG Data
doi: 10.1109/JTEHM.2016.2544298
Figure Lengend Snippet: Graphical representation of DWT decomposition. (HPF: High pass filter, LPF: Low pass filter.)
Article Snippet: NMSE is computed in dB using the equation: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}\begin{equation*} NMSE=20logE\left\{{\frac {\sum \left [{ x1\left ({ i }\right )-x2\left ({ i }\right ) }\right ]^{2}}{\sum \left [{ x1\left ({ i }\right ) }\right ]^{2}}}\right\} \end{equation*}\end{document} Time and frequency components can be analyzed simultaneously using the
Techniques:
Journal: IEEE Journal of Translational Engineering in Health and Medicine
Article Title: Comparative Study of Wavelet-Based Unsupervised Ocular Artifact Removal Techniques for Single-Channel EEG Data
doi: 10.1109/JTEHM.2016.2544298
Figure Lengend Snippet: Comparison of a section of EEG data from AF3 channel (Dataset 1) before and after denoising using SWT and DWT decomposition techniques with coif3 wavelet.
Article Snippet: NMSE is computed in dB using the equation: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}\begin{equation*} NMSE=20logE\left\{{\frac {\sum \left [{ x1\left ({ i }\right )-x2\left ({ i }\right ) }\right ]^{2}}{\sum \left [{ x1\left ({ i }\right ) }\right ]^{2}}}\right\} \end{equation*}\end{document} Time and frequency components can be analyzed simultaneously using the
Techniques: Comparison