Name and describe, in detail, 2 methods used to eliminate noise from a (spatio-temporal) signal.
This question requires a clear, detailed explanation of the methods. Mathematical equations can/should be minimized.
The application under consideration are signals from an EEG or MEG reading.© BrainMass Inc. brainmass.com October 10, 2019, 2:50 am ad1c9bdddf
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There are so many methods to eliminate noise from signals. This is infact an area of research of its own, with many applications in signal and image processing including the biomedical area. Wavelet transform thresholding (WTT) is a common technique used for signal and image denoising. The discrete wavelet transform uses two types of filters i.e.
averaging filters and detail filters. When we decompose a signal using the DWT, we are left with a set of wavelet coefficients that correlates to the high frequency sub-bands (which consist of the details in the data set). If these details are small enough, they might be omitted without substantially affecting the main features of the data set. Additionally, these small details are often those associated with noise; therefore, by setting these coefficients to zero, we are essentially killing the noise. This becomes the basic ...
This 1000 word solution provides a detailed description of two methods used to eliminate noise from a spatio-temporal signal. Additionally, it includes a complete list of reference sources for further investigation of the topic.