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A robust recursive technique for pole–zero system model order estimation
Author(s) -
AlSmadi Adnan
Publication year - 2000
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/1097-007x(200007/08)28:4<421::aid-cta112>3.0.co;2-w
Subject(s) - zero (linguistics) , eigenvalues and eigenvectors , range (aeronautics) , algorithm , signal (programming language) , covariance matrix , computer science , sequence (biology) , signal processing , noise (video) , process (computing) , matrix (chemical analysis) , mathematics , control theory (sociology) , engineering , digital signal processing , artificial intelligence , philosophy , materials science , image (mathematics) , aerospace engineering , linguistics , composite material , biology , genetics , operating system , control (management) , quantum mechanics , programming language , physics , computer hardware
Model order selection of a pole–zero system is an important area of research in signal processing and its results are applied in a wide range of disciplines of science and engineering problems such as speech analysis and spectrum estimation. This paper describes a method for estimating the model order of a pole–zero system. It looks at the minimum eigenvalue of a data covariance matrix derived from the observed data sequence. This algorithm is an expansion of the algorithm proposed by Liang et al. ( IEEE Trans. Signal Process 1993; 41 (10):3003–3009). Some simulation results are offered to justify that the proposed method is effective and performs well even at low signal‐to‐noise ratio (SNR). Copyright © 2000 John Wiley & Sons, Ltd.