An adaptive k-means clustering algorithm that approximates an optimal clustering solution with an efficient adaptive learning rate, which renders it usable in situations where the statistics of the problem task varies slowly with time.Expand

The authors present a modification of the traditional k-means clustering algorithm that approximates an optimal clustering solution with an adaptive learning rate.Expand

A modified k-means competitive learning algorithm that can perform efficiently in situations where the input statistics are changing, such as in nonstationary environments, is presented.Expand

In this Letter, 3Dadaptive regularisation Savitzky–Golay (3D ARSG) filter is proposed as the real-time filter for removing speckle noise in 3D-US imaging.Expand

We present in this paper a new method that adjusts the step-size of the LMS algorithm dynamically according to the uniformity among the variances of the fluctuations in the filter weights. This new… Expand

Abstract : In a layered feet-forward network the error surface with respect to a desired goal function completely describes the potential of that network to carry out a particular task. Such an error… Expand