caa a22 4500 606206426 CHVBK 20210128101011.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s00034-014-9923-1 doi (NATIONALLICENCE)springer-10.1007/s00034-014-9923-1 Clipped LMS/RLS Adaptive Algorithms: Analytical Evaluation and Performance Comparison with Low-Complexity Counterparts [Elektronische Daten] [Mehdi Bekrani, Mojtaba Lotfizad] The high computational load of conventional adaptive FIR filters applied to long system identification and their weak tracking ability has encouraged researchers to seek for efficient adaptive algorithms for this kind of applications. One of the efficient solutions is the three-level clipped LMS/RLS adaptive algorithm. In this paper, an insight into the performance of these adaptive algorithms that evaluates the amount of steady-state misalignment error of clipped LMS/RLS adaptive algorithms employed for identification of time-invariant and time-varying systems, is presented. Employing it, we compare the misalignment performance with their low-complexity adaptive algorithm counterparts theoretically. In addition, we derive the optimal step size/forgetting factor explicitly and also obtain a relation between the optimal level of the clipping and step size/forgetting factor to achieve the lowest steady-state misalignment and then we explain as to how to improve the performance of these kinds of adaptive algorithms by adjusting the clipping threshold according to the noise level in such a way that a higher performance is achieved. Finally, different adaptive algorithms have been further coded in VHDL in order to evaluate them in terms of speed and hardware resources. Springer Science+Business Media New York, 2014 Adaptive filter nationallicence Convergence rate nationallicence Misalignment nationallicence Clipping nationallicence System identification nationallicence Bekrani Mehdi Qom University of Technology, Qom, Iran aut Lotfizad Mojtaba Tarbiat Modares University, Tehran, Iran aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/5(2015-05-01), 1655-1682 0278-081X 34:5<1655 2015 34 34 https://doi.org/10.1007/s00034-014-9923-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9923-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bekrani Mehdi Qom University of Technology, Qom, Iran aut NATIONALLICENCE 700 1- Lotfizad Mojtaba Tarbiat Modares University, Tehran, Iran aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/5(2015-05-01), 1655-1682 0278-081X 34:5<1655 2015 34 34