DIGITAL ALGORITHMS FOR ANALOG ADAPTIVE FILTERS

The use of analog adaptive filters in modern integrated systems is limited by the complexity of the analog adaptation hardware and by dc offset effects which limit the adaptation accuracy. Both problems can be addressed by using an analog filter with a digital adaptation algorithm. The design of digitally programmable analog filters suitable for adaptive applications is examined. Novel Gm-C circuits are described and implemented in a CMOS prototype 5th order integrated filter with digitally programmable poles and zeros. However, the greatest challenge associated with performing digital adaptation of an analog filter is obtaining the gradient information without overcomplicating the analog design. Three main approaches to overcoming this challenge are described. First, the gradient information is obtained by correlating changes in the output squared error to independent dither on the adapted parameters. Second, the internal state signals (and, hence, the gradient signals) are calculated from a time delayed input vector using a co-ordinate transformation. Third, time delayed estimates of the filter input are obtained digitally from the filter output and used to calculate the required gradient signals. All three techniques use digital

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