论文信息 - Mean-square performance of adaptive filters using averaging theory

Mean-square performance of adaptive filters using averaging theory

This paper uses averaging analysis to study the mean-square performance of adaptive filters, not only in terms of stability conditions but also in terms of expressions for the mean-square error and the mean-square deviation of the filters, as well as in terms of the transient performance of the corresponding partially averaged systems. The treatment relies on energy conservation arguments. Simulation results illustrate the analysis and the derived performance expressions.

[1] J. Mazo. On the independence theory of equalizer convergence , 1979, The Bell System Technical Journal.

[2] Ali H. Sayed,et al. Fundamentals Of Adaptive Filtering , 2003 .

[3] Pierre Priouret,et al. Adaptive Algorithms and Stochastic Approximations , 1990, Applications of Mathematics.

[4] Ali H. Sayed,et al. A unified approach to the steady-state and tracking analyses of adaptive filters , 2001, IEEE Trans. Signal Process..

[5] Tamer Basar,et al. Analysis of Recursive Stochastic Algorithms , 2001 .

[6] Ralph K. Cavin,et al. Analysis of error-gradient adaptive linear estimators for a class of stationary dependent processes , 1982, IEEE Trans. Inf. Theory.

[7] Harold J. Kushner,et al. Approximation and Weak Convergence Methods for Random Processes , 1984 .

[8] Tareq Y. Al-Naffouri,et al. Transient analysis of data-normalized adaptive filters , 2003, IEEE Trans. Signal Process..

[9] Bruce E. Hajek,et al. Review of 'Approximation and Weak Convergence Methods for Random Processes, with Applications to Stochastic Systems Theory' (Kushner, H.J.; 1984) , 1985, IEEE Transactions on Information Theory.