By Ramaswamy Palaniappan
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Extra resources for Biological Signal Analysis
E. the segments overlap with M-D samples. Thus K=(N-M)/D +1 and the percentage overlap is 100*(M-D)/M. Next, we apply the conventional method to compute periodogram (or modified periodogram) for each segment and finally average all the periodograms. In MATLAB, pwelch function can be used where the percentage overlap is 50% with K=8 and Hamming window is used by default. As an example, let use revisit the ECG signal used earlier. The first plot is obtained by using the periodogram code given earlier, while the second is obtained by using pwelch function.
E. more samples). 5, we had to double N. e. we truncate the signal (though in actual fact, we do not). If the signal was indeed periodic, it would have the same starting and ending points after truncation. But for the CPU usage example, we would have discontinuity, so this creates a lot of noise, which is technically known as spectral leakage and can be solved using windowing. 15  can be used to force the signal values at the beginning and end to be the same. For most windows, this value is zero though not always.
9: (a) BPF (b) BSF of the three sinusoidal signals. e. apply a rectangular window; x Compute the Inverse Discrete Fourier Transform (IDFT). 10) and say, we wish to design a LPF with fp=10 Hz and fs=12 Hz. e. set the values y(7:95)=0. As MATLAB indexing starts from 1, y(1:6) represents DFT values from 0 to 10 Hz16, which represents the passband range, the stopband range from 12 Hz to 100 Hz is represented by y(7:51). 11 (a). 10: Combination of two sinusoidal signals (f1=8 Hz and f2=25 Hz). 5 123456 96 97 98 99 100 7 … ……..
Biological Signal Analysis by Ramaswamy Palaniappan