The author derives a useful information-theoretical technology from the tunable filter that automatically detects the frequency of an unknown signal in white Gaussian noise by adjusting its parameter to the correlation coefficient of its output. The tunable filter earlier proposed by S. He and B. Kedem (see ibid., vol.35, no.2, p.360-9, 1989) is known as the HK filter. The methodology sidesteps the white noise and normality assumptions. More importantly, it is shown that broad classes of linear filters can be made to implement the detection plan. In particular, bandpass filters can be expected to lock-in even more quickly and accurately than the HK filter. This analysis yields a formula for the error contraction at each recursion.>
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Sid Yakowitz (1991) studied this question.
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