Title :
A state-space approach to QRD-LSL interpolation and QRD-LSL smoothing
Author_Institution :
Dept. of Electr. Eng., Fu Jen Catholic Univ., Taipei, Taiwan
fDate :
11/1/2001 12:00:00 AM
Abstract :
Sayed and Kailath (1994) demonstrated the feasibility of directly deriving many known adaptive filtering algorithms in square-root forms by a proper reformulation of the original adaptive problem into a state-space form. This work employs this state-space form to develop adaptive interpolation and smoothing algorithms. In particular, a systematic and concise derivation of the QR-decomposition least-squares lattice (QRD-LSL) interpolation and smoothing algorithms using correspondences between Kalman filtering and LSL adaptive filtering is given
Keywords :
adaptive Kalman filters; interpolation; lattice filters; least squares approximations; smoothing methods; state-space methods; Kalman filtering; LSL adaptive filtering; QR-decomposition least-squares lattice interpolation; QR-decomposition least-squares lattice smoothing; QRD-LSL interpolation; QRD-LSL smoothing; adaptive filtering algorithms; adaptive interpolation; quadratic residue algorithms; square-root forms; state-space approach; Adaptive filters; Filtering algorithms; Information filtering; Information filters; Interpolation; Kalman filters; Resonance light scattering; Smoothing methods; State estimation; Vectors;
Journal_Title :
Signal Processing, IEEE Transactions on
