Title :
On the Steady-State Analysis of PNLMS-Type Algorithms for Correlated Gaussian Input Data
Author :
Kuhn, Eduardo Vinicius ; Das Chagas De Souza, Francisco ; Seara, Rui ; Morgan, D.R.
Author_Institution :
Dept. of Electr. Eng., Fed. Univ. of Santa Catarina, Florianópolis, Brazil
Abstract :
This letter presents model expressions describing the steady-state behavior of proportionate normalized least-mean-square (PNLMS)-type algorithms, taking into account both complex- and real-valued correlated Gaussian input data. Specifically, based on energy-conservation arguments, general expressions for the excess mean-square error (EMSE) in steady state and misadjustment are obtained. Such general expressions are then applied to two well-known PNLMS-type algorithms, namely the improved PNLMS (IPNLMS) and the individual-activation-factor PNLMS (IAF-PNLMS). Simulation results are shown confirming the accuracy of the proposed model expressions under different operating conditions.
Keywords :
Gaussian processes; adaptive filters; correlation theory; least mean squares methods; EMSE; IAF-PNLMS; IPNLMS; adaptive filters; correlated Gaussian input data; energy conservation arguments; excess mean square error; improved PNLMS algorithm; individual activation factor PNLMS; proportionate normalized least mean square; steady-state analysis; Accuracy; Algorithm design and analysis; Data models; Prediction algorithms; Signal processing algorithms; Signal to noise ratio; Steady-state; Adaptive filtering; excess mean-square error; misadjustment; proportionate normalized least-mean-square algorithm; steady-state behavior; stochastic model;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2332751
