.

To remedy the filtering degradation problem, a robust filter named as the KFLMS,

which has good noise rejection property for such systems, is developed in this paper,

where the UI estimates are obtained by using least mean square algorithm...

when the underlying distribution follows the proportional

hazard rate model. Various point estimators are obtained in each sampling

schemes and compared with respect to mean squared error and Pitman

measure of closeness criteria...

Process capability and incapability indices are numerical tools that evaluate the ability of a process in conformance with the required specifications. The process incapability index C\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ ...

on radial distribution functions and mean squared displacement are evidence on the process of dispersing at nano scale....

are applied to test image. The proposed method includes

fuzzy clustering part for clustering the observed vector of each pixel into one of M mutually exclusive

blocks. In the training phase, Least Mean Square (LMS) algorithm use to train center...

Abstract: Data reusing normalized least mean

squares (DRNLMS) algorithms converge often faster

than the conventional least mean squares (LMS)

algorithm. This paper analyzes an adaptive DRNLMS,

ADRNLMS, algorithm which has...

In this paper, a new median filter switcher is presented for suppression of impulsive noise

in gray-level images. The proposed filter is Modified Adaptive Center Weighted Median

(MACWM) filter with an adjustable ...