In this paper we propose a very simple FIR pre-filter based method for near optimal least-squares linear approximation of discrete time signals. A digital pre-processing filter,...
Marco Dalai, Riccardo Leonardi, Pierangelo Miglior...
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...