Implement the lms adaptive filter algorithm

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Reference no: EM131190191

Assignment

In this assignment, you will be provided with a file containing four channels of recorded data. The channels are:

1. Left eye electrooculogram (EOG) measurements;
2. Right eye EOG measurements;
3. Left side EEG measurements;
4. Right side EEG measurements.

The data was collected simultaneously over a 20 minute period. The sample rate was 200 samples/sec and I have downsampled the data by a factor of 2, resulting in an effective sample rate of 100 samples/sec. The frequency content of the signals thus lies between zero and 50 Hz. The low-pass filter used for the decimation process has a cutoff frequency of around 40 Hz, so frequencies between 40 and 50 Hz are suppressed. The data is contained in the 120000×4 array ‘y' in the matlab binary file "EEG EOG Example1 ds.mat" 1 provided on MyUni.

The objectives of this assignment are:

1. To perform preliminary "standard" signal analysis on the data using matlab tools in order to understand spectral and correlation properties of the data, and to validate its suitability for adaptive filtering ;

2. To implement the LMS adaptive filter algorithm for interference cancellation in matlab ;

3. To process suitable pairs of data using the LMS adaptive filter to ameliorate the effects of eye-movements on the measured EEG signals;

4. To investigate what the effect of adaptive filtering has on the EEG signals and whether we can conclude that adaptive filtering might be a useful tool for researchers in this area.

Please note that you are not required to make any conclusions about the structure of the processed EEG signals as they pertain to the medical application.

Review Article - Removal of ocular artifact from the EEG: a review - R.J. Croft*, R.J.Barry

Attachment:- Assignment.rar

Reference no: EM131190191

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