Title :
Continuous-time recursive least-squares estimation, adaptive neural networks and systolic arrays
Author :
Dehaene, Jeroen ; Moonen, Marc ; Vandewalle, Joos
fDate :
2/1/1995 12:00:00 AM
Abstract :
We derive square-root covariance-type and information-type algorithms for continuous-time recursive least-squares estimation. The algorithms allow for easy manipulation and uniform parallelization. They are related to well-known neural adaptation laws and can be considered as continuous-time limits of systolic arrays
Keywords :
least squares approximations; neural nets; parallel algorithms; recursive estimation; systolic arrays; adaptive neural networks; continuous-time limits; continuous-time recursive estimation; covariance-type; information-type; neural adaptation laws; recursive least-squares estimation; square-root algorithms; systolic arrays; uniform parallelization; Adaptive systems; Covariance matrix; Iterative algorithms; Laboratories; Least squares approximation; Matrix decomposition; Neural networks; Recursive estimation; Solids; Systolic arrays;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
