On the inconsistency of IQML

The IQML (iterative quadratic maximum likelihood) algorithm is a popular iterative algorithm used in temporal and spatial frequency estimation problems to approximate the global minimizer of the deterministic maximum likelihood criterion. In this paper, w

[1]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[2]  James H. McClellan,et al.  Exact equivalence of the Steiglitz-McBride iteration and IQML , 1991, IEEE Trans. Signal Process..

[3]  Yingbo Hua The most efficient implementation of the IQML algorithm , 1994, IEEE Trans. Signal Process..

[4]  Petre Stoica,et al.  Markov-based eigenanalysis method for frequency estimation , 1994, IEEE Trans. Signal Process..

[5]  Petre Stoica,et al.  Maximum likelihood methods for direction-of-arrival estimation , 1990, IEEE Trans. Acoust. Speech Signal Process..

[6]  Jian Li,et al.  Comparative study of IQML and MODE direction-of-arrival estimators , 1998, IEEE Trans. Signal Process..

[7]  P. Stoica,et al.  Novel eigenanalysis method for direction estimation , 1990 .

[8]  Jian Li,et al.  Comparative study of IQML and MODE for direction-of-arrival estimation , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Yoram Bresler,et al.  Exact maximum likelihood parameter estimation of superimposed exponential signals in noise , 1986, IEEE Trans. Acoust. Speech Signal Process..

[10]  Ramdas Kumaresan,et al.  An algorithm for pole-zero modeling and spectral analysis , 1986, IEEE Trans. Acoust. Speech Signal Process..

[11]  Petre Stoica,et al.  Performance analysis of an adaptive notch filter with constrained poles and zeros , 1988, IEEE Trans. Acoust. Speech Signal Process..

[12]  T. Söderström,et al.  The Steiglitz-McBride identification algorithm revisited--Convergence analysis and accuracy aspects , 1981 .

[13]  Louis L. Scharf,et al.  On the complexity of IQML algorithms , 1992, IEEE Trans. Signal Process..