Title :
Symmetric alpha-stable filter theory
Author :
Bodenschatz, John S. ; Nikias, Chrysostomos L.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fDate :
9/1/1997 12:00:00 AM
Abstract :
Symmetric α-stable (SαS) processes are used to model infinite-variance impulsive noise. In general, Wiener filter theory is not meaningful in (SαS) environments because the expectations may be unbounded. To develop a theory for linear finite impulse response systems with independent identically distributed (SαS) inputs, we propose median orthogonality as a linear filter criterion, derive a generalized Wiener-Hopf solution equation, and show a sufficient condition for a filter to achieve the criterion. For non-Gaussian (SαS) densities, zero-forcing least-mean-squares is the only well-known filter that satisfies the criterion, but others can be designed. We present a second algorithm and simulations showing that both converge to the generalized Wiener-Hopf solution
Keywords :
FIR filters; integral equations; least mean squares methods; linear systems; noise; SαS processes; generalized Wiener-Hopf solution; generalized Wiener-Hopf solution equation; i.i.d. systems; independent identically distributed inputs; infinite-variance impulsive noise; linear filter criterion; linear finite impulse response systems; median orthogonality; nonGaussian densities; symmetric α-stable processes; symmetric alpha-stable filter theory; zero-forcing least-mean-squares; Adaptive filters; Equations; Filtering theory; Finite impulse response filter; Iterative algorithms; Nonlinear filters; Signal processing algorithms; Vectors; Wiener filter; Working environment noise;
Journal_Title :
Signal Processing, IEEE Transactions on