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New fading memory fast SRLS algorithm for 2-D SAR model parameter estimation

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2 Author(s)
Ping-Ya Zhao ; Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada ; Litva, J.

We present a new fast spatially recursive least-squares (SRLS) algorithm with exponentially fading memory for adaptive estimation of two-dimensional (2-D) nonstationary simultaneous autoregressive (SAR) model parameters. The computational complexity of the new algorithm is 8m3/2+6m multiplications and divisions per recursion (MADPR) in contrast with 15m3/2+16m MADPR of the best existing algorithm, where m is the number of the estimated model parameters. The new algorithm has the same statistical properties and tracking capability, compared with the existing algorithms. The derivation of the algorithm and the computer simulation results are given in the paper

Published in:

Electrical and Computer Engineering, 1993. Canadian Conference on

Date of Conference:

14-17 Sep 1993