Reduced complexity recursive least square lattice structure adaptive filter by means of limited recursion of the backward and forward error prediction squares

A method for reducing computational complexity of an in-stage adaptive filter, the method comprising:

• receiving an input signal at an input interface of the adaptive filter;
• filtering the input signal by a processor operative in conjunction with stored data and instructions for each stage of the adaptive filter, to produce a filtered signal, including
• updating recursively a forward error prediction square term for a first portion of a length of the adaptive filter;
• updating recursively a backward error prediction square term for the first portion of the length of the adaptive filter;
• and
• keeping the updated forward and backward error prediction square terms constant for a second portion of the length of the adaptive filter;
• and
• providing the filtered signal at an output interface of the adaptive filter.

An m-stage adaptive filter comprising:

• an interface to receive an input signal;
• a processor operative in conjunction with stored data and instructions to recursively update filter coefficients for each stage of the adaptive filter while producing a filtered signal, the processor configured to
• reduce a number of updates of the forward error prediction squares and backward error prediction squares of the filter coefficients by performing the updates up to a predefined number of stages of the adaptive filter, and
• hold the forward error prediction squares and the backward error prediction squares constant during the remainder of the stages of the adaptive filter;
• and
• an interface to provide the filtered signal as an output signal.