%0 Journal Article
	%A Shazia Javed and  Noor Atinah Ahmad
	%D 2012
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 72, 2012
	%T An Estimation of the Performance of HRLS Algorithm
	%U https://publications.waset.org/pdf/11855
	%V 72
	%X The householder RLS (HRLS) algorithm is an O(N2)
algorithm which recursively updates an arbitrary square-root of the
input data correlation matrix and naturally provides the LS weight
vector. A data dependent householder matrix is applied for such
an update. In this paper a recursive estimate of the eigenvalue
spread and misalignment of the algorithm is presented at a very low
computational cost. Misalignment is found to be highly sensitive to
the eigenvalue spread of input signals, output noise of the system and
exponential window. Simulation results show noticeable degradation
in the misalignment by increase in eigenvalue spread as well as
system-s output noise, while exponential window was kept constant.
	%P 1665 - 1667