Title

Two-Dimensional, Frequency Domain, Adaptive System Modeling Using Three-Dimensional Spatiotemporal Inputs

Abstract

In this paper, an adaptive, frequency domain, steepest descent algorithm for two-dimensional (2-D) system modeling is presented. The algorithm is derived here for the equation error model, and models the 2-D spatially linear and invariant unknown system by a 2-D auto-regressive, moving-average (ARMA) process. The proposed technique is implemented in the 3-D spatiotemporal domain. At each iteration, corresponding to a given pair of input and output images, the algorithm is formulated to minimize the energy of an error-function in the frequency-domain by adjusting the coefficients of the 2-D ARMA model. Signal dependent, optimal convergence factors, referred to as the homogenous convergence factors, are developed. Computer simulations demonstrate the algorithm’s excellent adaptation accuracy and convergence speed. For illustration, the proposed algorithm is successfully applied to modeling a time varying 2-D system. © 1995 IEEE.

Publication Date

1-1-1995

Publication Title

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing

Volume

42

Issue

5

Number of Pages

317-325

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/82.386171

Socpus ID

0347103827 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0347103827

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