Figure 14. The signal at the top left seems to be only random noise, but its power spectrum (top right) shows that high-frequency components dominate the signal. The power spectrum is expanded in the X and Y directions ( bottom left) to show more clearly the low-frequency region. Working on the hypothesis that the components above the 20th harmonic are noise, the Fourier filter function can be used to delete the higher harmonics and to reconstruct the signal from the first 20 harmonics. The result (bottom right) shows the signal contains two bands at about x=200 and x=300 that are totally obscured by noise in the original signal.
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The custom Matlab function FouFilter.m is a more flexible Fourier filter that can serve as a lowpass, highpass, bandpass, or bandreject (notch) filter with variable cut-off rate. Has the form The Interactive Fourier Filter for Matlab function has sliders that allow you to adjust the Fourier filter parameters (center frequency, filter width, and cut-off rate) while observing the effect on the signal output dynamically. It can handle signals of virtually any length, limited only by the memory in your computer. Requires Matlab 6.5. |