### Abstract

Adaptive signal processing algorithms are often used in order to ″track″ an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow LMS algorithm is apparently the most frequently used. This work develops an upper bound on the norm-squared error between the parameter vector being tracked and the value obtained by the algorithm. The upper bound illustrates the relationship between the algorithm step-size and the maximum rate of variation in the parameter vector. Finally, some simple covariance decay-rate conditions are imposed to obtain a bound on the mean square error.

Original language | English (US) |
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Pages | 466-469 |

Number of pages | 4 |

State | Published - Jan 1 1980 |

Event | Unknown conference - Denver, CO, USA Duration: Apr 9 1980 → Apr 11 1980 |

### Other

Other | Unknown conference |
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City | Denver, CO, USA |

Period | 4/9/80 → 4/11/80 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*TRACKING PROPERTIES OF ADAPTIVE SIGNAL PROCESSING ALGORITHMS.*. 466-469. Paper presented at Unknown conference, Denver, CO, USA, .

**TRACKING PROPERTIES OF ADAPTIVE SIGNAL PROCESSING ALGORITHMS.** / Farden, David C.; Sayood, Khalid.

Research output: Contribution to conference › Paper

}

TY - CONF

T1 - TRACKING PROPERTIES OF ADAPTIVE SIGNAL PROCESSING ALGORITHMS.

AU - Farden, David C.

AU - Sayood, Khalid

PY - 1980/1/1

Y1 - 1980/1/1

N2 - Adaptive signal processing algorithms are often used in order to ″track″ an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow LMS algorithm is apparently the most frequently used. This work develops an upper bound on the norm-squared error between the parameter vector being tracked and the value obtained by the algorithm. The upper bound illustrates the relationship between the algorithm step-size and the maximum rate of variation in the parameter vector. Finally, some simple covariance decay-rate conditions are imposed to obtain a bound on the mean square error.

AB - Adaptive signal processing algorithms are often used in order to ″track″ an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow LMS algorithm is apparently the most frequently used. This work develops an upper bound on the norm-squared error between the parameter vector being tracked and the value obtained by the algorithm. The upper bound illustrates the relationship between the algorithm step-size and the maximum rate of variation in the parameter vector. Finally, some simple covariance decay-rate conditions are imposed to obtain a bound on the mean square error.

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UR - http://www.scopus.com/inward/citedby.url?scp=0019210597&partnerID=8YFLogxK

M3 - Paper

SP - 466

EP - 469

ER -