Time-dependent adaptive filters (TDAFs) that allow for the cyclostationary nature of communication signals by periodically changing the filter and adaptation parameters are examined. The TDAF has an advantage over the conventional time-independent adaptive filter in achieving better performance, i.e. reduced mean square error (MSE), for signals with periodic statistics. The basic theory of the TDAF is presented. The TDAF is shown to be more effective than the time-independent adaptive filter for interference rejection. This is verified by theoretical analysis and computer simulation of specific cases of extracting a signal in noise or interference. The criteria for judging the performance of the TDAF for interference rejection are MSE, bit error rate measurements, and constellation diagrams.>
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Reed et al. (1990) studied this question.
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