Stochastic Model for the Mean Weight Evolution of the IAF-PNLMS Algorithm

• Published in: IEEE transactions on signal processing Vol. 58; no. 11; pp. 5895 - 5901
• Main Authors: das Chagas de Souza, Francisco, Tobias, Orlando José, Seara, Rui, Morgan, Dennis R
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Algorithms; Applied sciences; Brazil Council; Circuits; Computer simulation; Electronic mail; Evolution; Exact sciences and technology; Gain; IAF-PNLMS algorithm; Information, signal and communications theory; Laboratories; Mathematical model; Mathematical models; mean weight evolution; Miscellaneous; Permission; Phases; Prediction algorithms; Signal processing; Signal processing algorithms; stochastic model; Stochastic processes; Stochasticity; Telecommunications and information theory; Stochastic model; mean weight evolution; Input signal; Unsteady state; Algorithm; Modeling; Steady state; Time variation; IAF-PNLMS algorithm; Accuracy; Simulation; Signal processing; Least mean squares methods
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2010.2063428

This correspondence studies the adaptive weight evolution of the individual-activation-factor proportionate normalized least-mean-square (IAF-PNLMS) algorithm. For such, the modeling methodology used considers that the gain matrix is time varying and the input signal is not restricted to be white. A model is obtained that predicts the algorithm mean weight behavior for both transient and steady-state phases. Through simulation results, the accuracy of the proposed model is verified. In addition, the approach developed here is general and can be applied to other PNLMS-type algorithms.