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This paper presents an efficient adaptive algorithm for designing FIR digital filters that are efficient according to an Lp error criteria. The algorithm is an extension of Burrus' iterative reweighted least-squares (IRLS) method for approximating Lp filters. Such algorithm will converge for most significant cases in a few iterations. In some cases however,(More)
This paper introduces an iterative algorithm for designing IIR digital filters that minimize a complex approximation error in an £ ¥ ¤ sense. The algorithm combines ideas that have proven successful in the similar problem of £ ¦ ¤ FIR filter design. We use iterative prefiltering techniques common in applications such as parameter estimation together with an(More)
This paper presents a family of algorithms to design FIR and IIR digital filters using l<inf>p</inf> norms as optimality criteria. The algorithms presented are based on the Iterative Reweighted Least Squares (IRLS) method, and enjoy the same flexibility that traditional IRLS methods have. While other FIR methods use l<inf>2</inf> or l<inf>¿</inf> norms as(More)
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