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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cho, S.H. Mathews, V.J. |
| Copyright Year | 1990 |
| Description | Author affiliation: Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA (Cho, S.H.; Mathews, V.J.) |
| Abstract | A tracking analysis of adaptive filters equipped with the sign algorithm and operating in nonstationary environments is presented. By modeling the nonstationarity as a random disturbance, it is shown that the long-term time-average of the mean-absolute estimation error is bounded for all finite and positive values of the convergence parameter mu , and that there exists an optimal choice of mu such that this bound is minimized. By making use of the commonly used independence assumption and further assuming that the nonstationarity is solely due to the time-varying behavior of the optimum coefficients caused by a stationary random disturbance, it is shown that the probability distribution functions of the successive coefficient misalignment vectors converge to a stationary limiting distribution. Finally, by further assuming that the signals involved are zero-mean and Gaussian, a set of nonlinear difference equations that characterizes the mean and mean-squared behavior of the filter coefficients and the mean-squared estimation error during the adaptation and tracking operations is derived.< |
| Starting Page | 869 |
| Ending Page | 872 |
| File Size | 437632 |
| Page Count | 4 |
| File Format | |
| DOI | 10.1109/MWSCAS.1989.101993 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1989-08-14 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Estimation error Adaptive filters Convergence Probability distribution Difference equations Cities and towns Least squares approximation Filtering algorithms Adaptive algorithm |
| Content Type | Text |
| Resource Type | Article |
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