Title :
A stability result for RLS adaptive bilinear filters
Author :
Lee, Junghsi ; Mathews, V.John
Author_Institution :
Adv. Technol. Center, Ind. Technol. Res. Inst., Hsinchu, Taiwan
Abstract :
The article considers recursive least squares (RLS) adaptive nonlinear filtering using bilinear system models. It is shown that the extended RLS adaptive bilinear filter, as well as the equation-error RLS adaptive bilinear filter, are guaranteed to be stable in the sense that the time average of the squared estimation error is bounded whenever the underlying process that generates the input signals is stable in the same sense.<>
Keywords :
adaptive filters; bilinear systems; filtering theory; least squares approximations; nonlinear filters; recursive filters; stability; RLS adaptive bilinear filters; adaptive nonlinear filtering; bilinear system models; equation-error RLS filter; extended RLS filter; input signals; recursive least squares; squared estimation error; stability; time average; Adaptive filters; Estimation error; Filtering; Least squares methods; Nonlinear equations; Nonlinear systems; Resonance light scattering; Signal generators; Signal processing; Stability;
Journal_Title :
Signal Processing Letters, IEEE
