K. Takahashi et al., CONVERGENCE ANALYSIS OF QUANTIZING METHOD WITH CORRELATED GAUSSIAN DATA, IEICE transactions on fundamentals of electronics, communications and computer science, E79A(8), 1996, pp. 1157-1165
Citations number
13
Categorie Soggetti
Engineering, Eletrical & Electronic","Computer Science Hardware & Architecture","Computer Science Information Systems
In this paper the normalized least mean square (NLMS) algorithm based
on clipping input samples with an arbitrary threshold level is studied
. The convergence characteristics of these clipping algorithms with co
rrelated data are presented. In the clipping algorithm, the input samp
les are clipped only when the input samples are greater than or equal
to the threshold level and otherwise the input samples are set to zero
. The results of the analysis yield that the gain constant to ensure c
onvergence, the speed of the convergence, and the misadjustment are fu
nctions of the threshold level. Furthermore an optimum threshold level
is derived in terms of the convergence speed under the condition of t
he constant misadjustment.