Asymptotic analysis of the underdetermined recursive least-squares algorithm

The asymptotic analysis of the Underdetermined Recursive Least-Squares (URLS) algorithm is performed. In particular, the behaviour of the weight-error correlation matrix is investigated and the misadjustment is calculated. For highly correlated input signals the misadjustment is shown to be inversely proportional to the minimum eigenvalue of the underdetermined order autocorrelation matrix. Simulations are included to justify the conclusions.