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Convergence models for lattice joint process estimators and least squares algorithms

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1 Author(s)
Honig, M.L. ; Bell Laboratories, Holmdel, NJ

A simple model characterizing the convergence properties of an adaptive digital lattice filter using gradient algorithms has been reported [1]. This model is extended to the least mean square (LMS) lattice joint process estimator [5], and to the least squares (LS) lattice and "fast" Kalman algorithms [9] -[16]. The models in each case are compared with computer simulation. The single-stage LMS lattice analysis presented in [1] is also applied to the LS lattice. Results indicate that for stationary inputs, the LMS lattice and LS algorithms exhibit similar behavior.

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Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:31 ,  Issue: 2 )