A new adaptive algorithm to reduce weight fluctuations caused by high variance data

A new adaptive algorithm to reduce weight fluctuations caused by high variance data

A nongradient iterative algorithm that has reduced adaptive filter weight fluctuations caused by high variance input data is presented. The algorithm adapts a single weight at each time step and has approximately the same computational requirements as the LMS algorithm.< >

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Veröffentlicht in:IEEE transactions on signal processing 1992-09, Vol.40 (9), p.2324-2327
Hauptverfasser: Cilke, J.T., Etter, D.M.
Format: Artikel
Sprache:eng
Schlagworte:
Adaptive algorithm
Adaptive filters
Convergence
Equations
Finite impulse response filter
Fluctuations
Gaussian processes
Noise cancellation
Predictive models
Signal processing algorithms
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Zusammenfassung:A nongradient iterative algorithm that has reduced adaptive filter weight fluctuations caused by high variance input data is presented. The algorithm adapts a single weight at each time step and has approximately the same computational requirements as the LMS algorithm.< >
ISSN:1053-587X
1941-0476
DOI:10.1109/78.157274