A new class of adaptive nonlinear filters was developed.

Fuzzy membership functions based on different distance measures were adopted to determine the weights of new nonlinear, adaptive filters.

A unique feature of an adaptive filter is that its coefficient can be updated online according to some optimization criterion.

The theory of linear adaptive filters has reached a highly mature stage of development.

However, the same can not be said about nonlinear adaptive filters,.

It is an adaptive filter that examines large amounts of sample unacceptable text, then scans for similar patterns in incoming comments.

The adaptive filter uses feedback in the form of an error signal to refine its transfer function to match the changing parameters.

To circumvent this potential loss of information, an adaptive filter could be used.

To remove this, an adaptive filter can be used to remove the direct signal in a process similar to active noise control.

Recent solution applies an adaptive filter to the robot's logic.