(1). Generate a sine wave y(t) = sin(2 . t +7 . a) Let f=10 H: Using randn to generate a random number for a (2). Generate noise with Gaussian distribution and with mean-0 and standard deviation-0.3. (3). Add the noise onto the sine wave y(t) (4). Repeat steps (1), (2) and (3) ten times, so you will get y,(t), y2(0),.. y10(t). Note each time the value of a is randomly changed by the MATLAB function randn (5). Average the 10 sets of data. See if the noise is reduced and how about the sine wave. (6). Calculate RMS and std for all the data including y mean(), yi(t), y2().. y10(t) Compare your results with the results you get from the problem 2