Abstract

A novel adaptive LMS (least mean square) algorithm is presented in which the algorithm can update the filter coefficients along both the horizontal and the vertical directions on a 2-D plane. Both the conventional algorithm and the new 2-D LMS algorithm are applied to the identification of unknown 2-D systems with stationary or nonstationary characteristics. The learning curves and the mean square errors show that the new 2-D LMS adaptive algorithm is particularly suitable for processing 2-D nonstationary signals. However, it converges slowly for stationary inputs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.