Abstract
This paper is concerned with the application of forward Orthogonal Least Squares (OLS) algorithm to the design of Finite Impulse Response (FIR) filters. The focus of this study is a new FIR filter design procedure and to compare this with traditional methods known as the fir2() routine provided by MATLAB.
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Xiao-Feng Wu received both the B.Eng. and M.Eng. degrees in electrical engineering from Xian Jiaotong University, Xian, China in 2000 and 2003, respectively. He is currently pursuing the Ph.D. degree at the University of Sheffield, UK.
His research interests include nonlinear system in frequency domain, signal processing, embedded system and real-time system.
Zi-Qiang Lang received his BSc and MSc degrees in China, and PhD degree at the University of Sheffield, UK. He is currently a lecturer in the Department of Automatic Control and Systems Engineering at Sheffield. His main expertise relates to the subject areas of industrial process control, modelling, identification and signal processing, and nonlinear system frequency domain analysis and designs. He has published more than 30 papers in this field most of which are publications in high quality learned journals. Dr Lang’s research results have been widely cited, and some basic ideas have been followed by many researchers working in related areas.
Stephen A Billings received the BEng degree in Electrical Engineering with first class honours from the University of Liverpool in 1972, the degree of PhD in Control Systems Engineering from the University of Sheffield in 1976, and the degree of DEng from the University of Liverpool in 1990. He is a Chartered Engineer [CEng], Chartered Mathematician [CMath], Fellow of the IEE and Fellow of the Institute of Mathematics and its Applications.
He was appointed as Professor in the Department of Automatic Control and Systems Engineering, University of Sheffield, UK in 1990 and leads the Signal Processing and Complex Systems research group. His research interests include system identification and information processing for nonlinear systems, narmax methods, model validation, prediction, spectral analysis, adaptive systems, nonlinear systems analysis and design, neural networks, wavelets, fractals, machine vision, cellular automata, spatio-temporal systems, fMRI and optical imagery of the brain, metabolic systems engineering, systems biology and related fields.
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Wu, XF., Lang, ZQ. & Billings, S.A. An Orthogonal Least Squares based approach to FIR designs. Int J Automat Comput 2, 163–170 (2005). https://doi.org/10.1007/s11633-005-0163-5
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DOI: https://doi.org/10.1007/s11633-005-0163-5