Title :
A relationship between the recursive least squares update and homotopy continuation methods
Author :
Stonick, Virginia L. ; Alexander, S.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fDate :
2/1/1991 12:00:00 AM
Abstract :
The authors present an alternative derivation of the general recursive least squares (RLS) algorithm using homotopy approaches. Homotopy continuation methods are briefly described, and a simple iterative update for path following is derived. A homotopy function is then constructed using the RLS filtering criteria. The equivalence between the iterative update for following the path defined by this homotopy function and the general RLS update is derived. Finally, an intuitive explanation of this result is presented
Keywords :
adaptive filters; filtering and prediction theory; iterative methods; least squares approximations; signal processing; RLS; RLS filtering criteria; homotopy continuation methods; homotopy function; iterative update; path following; recursive least squares update; signal processing; Adaptive arrays; Adaptive signal processing; Array signal processing; Equations; Least squares methods; Polynomials; Resonance light scattering; Signal processing algorithms; Speech processing; Vectors;
Journal_Title :
Signal Processing, IEEE Transactions on