b. Using MATLAB, get a list of variables in the file, i.e.,
whos
c. Using MATLAB, plot x 1 (t). i.e.,
plot(x1);
d. Disregarding the noise-like variations, the signal has clear periodicity
in it. Manually measure the time of one complete period of oscillation
(i.e.,  period T). Knowing that frequency is defined as the reciprocal of the
period, i.e., f = 1/T, calculate the dominant frequency of the variations.
In practical applications, manual frequency analysis becomes impossible.
Signal processing techniques to extract the dominant frequencies of a signal
(mainly using Fourier analysis) are heavily used in signal processing and
will be covered in Chapter 2.
e. Using MATLAB, plot x 2 (t) and x 3 (t). Then, manually calculate the average
slope of each of the signals. For each signal, identify if the slope exceeds 5.
Calculation of slopes is a fundamental operation commonly used in signal
and image processing, for example, a sharp slope of pixel intensity in any
direction often identifies the border between two parts of an image representing two separate regions or objects. Efficient techniques for slope and gradient analysis are discussed in the following chapters.
14
Biomedical Signal and Image Processing