It is known that signals (which could be functions ofspaceortime) belonging to𝕃2-space cannot be localized simultaneously in space/time and frequency domains. Alternatively, signals have a positive lower bound on theproductof theireffective spatial andeffective spectral widths, for simplicity, hereafter called theeffective space-bandwidthproduct(ESBP). This is the classical uncertainty inequality (UI), attributed to many, but, from a signal processing perspective, to Gabor who, in his seminal paper, established the uncertainty relation and proposed a joint time-frequency representation in which the basis functions have minimal ESBP. It is found that the Gaussian function is the only signal that has thelowestESBP. Since the Gaussian function is not bandlimited, no bandlimited signal can have the lowest ESBP. We deal with the problem of determining finite-energy, bandlimited signals which have the lowest ESBP. The main result is as follows. By choosing the convolution product of a Gaussian signal (withσas the variance parameter) and a bandlimited filter with a continuous spectrum, we demonstrate that there exists a finite-energy, bandlimited signal whose ESBP can be made to be arbitrarily close (dependent on the choice ofσ) to the optimal value specified by the UI.
On the uncertainty inequality as applied to discrete signals