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IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 3, MARCH 2003 639 Transient Analysis of Data-Normalized
 

Summary: IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 3, MARCH 2003 639
Transient Analysis of Data-Normalized
Adaptive Filters
Tareq Y. Al-Naffouri and Ali H. Sayed, Fellow, IEEE
Abstract--This paper develops an approach to the transient
analysis of adaptive filters with data normalization. Among other
results, the derivation characterizes the transient behavior of such
filters in terms of a linear time-invariant state-space model. The
stability of the model then translates into the mean-square stability
of the adaptive filters. Likewise, the steady-state operation of the
model provides information about the mean-square deviation
and mean-square error performance of the filters. In addition
to deriving earlier results in a unified manner, the approach
leads to stability and performance results without restricting the
regression data to being Gaussian or white. The framework is
based on energy-conservation arguments and does not require an
explicit recursion for the covariance matrix of the weight-error
vector.
Index Terms--Adaptive filter, data nonlinearity, energy-con-
servation, feedback analysis, mean-square-error, stability,

  

Source: Al-Naffouri, Tareq Y. - Electrical Engineering Department, King Fahd University of Petroleum and Minerals
Sayed, Ali - Electrical Engineering Department, University of California at Los Angeles

 

Collections: Engineering