Title

Adaptive, Frequency Domain, 2-D Modeling Using Spatiotemporal Signals

Abstract

In this paper, an adaptive, frequency domain, steepest descent algorithm for two-dimensional (2-D) system modeling is presented. Based on the equation error model, the algorithm, which characterizes the 2-D spatially linear and invariant unknown system by a 2-D auto-regressive, moving-average (ARMA) process, is derived and implemented in the 3-D spatiotemporal domain. At each iteration, corresponding to a given pair of input and output 2-D signals, the algorithm is formulated to minimize the error-function's energy in the frequency domain by adjusting the 2-D ARMA model parameters. A signal dependent, optimal convergence factor, referred to as the homogeneous convergence factor, is developed. It is the same for all the coefficients but is updated once per iteration. The resulting algorithm is called the Two-Dimensional, Frequency Domain, with Homogeneous μ*, Adaptive Algorithm (2D-FD-HAA). In addition, the algorithm is implemented using the 2-D Fast Fourier Transform (FFT) to enhance the computational efficiency. 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.

Publication Date

1-1-1996

Publication Title

Journal of Circuits, Systems and Computers

Volume

6

Issue

4

Number of Pages

351-358

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1142/S0218126696000236

Socpus ID

3042995620 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/3042995620

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