Title :
A new adaptive algorithm to reduce weight fluctuations caused by high variance data
Author :
Cilke, J. Thomas ; Etter, Delores M.
Author_Institution :
Houston Tracker Syst., Englewood, CO, USA
fDate :
9/1/1992 12:00:00 AM
Abstract :
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
Keywords :
adaptive filters; filtering and prediction theory; iterative methods; adaptive algorithm; computational requirements; high variance input data; iterative methods; nongradient iterative algorithm; reduced adaptive filter weight fluctuations; time step; Adaptive algorithm; Adaptive filters; Convergence; Equations; Finite impulse response filter; Fluctuations; Gaussian processes; Noise cancellation; Predictive models; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
