2-Dimensional, Frequency-Domain, Adaptive System Modeling Using 3-Dimensional Spatiotemporal Inputs

    Authors

    W. B. Mikhael;H. P. Yu

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    IEEE Trans. Circuits Syst. II-Analog Digit. Signal Process.

    Keywords

    Time-Varying Signals; Representation; Filter; Speech; Engineering, Electrical & Electronic

    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.

    Journal Title

    Ieee Transactions on Circuits and Systems Ii-Analog and Digital Signal Processing

    Volume

    42

    Issue/Number

    5

    Publication Date

    1-14-1995

    Document Type

    Article

    Language

    English

    First Page

    317

    Last Page

    325

    WOS Identifier

    WOS:A1995QZ03000002

    ISSN

    1057-7130

    Share

    COinS