Data-Reuse Recursive Least-Squares Algorithms
Constantin Paleologu, Jacob Benesty, Silviu Ciochină
Abstract
There are different strategies to improve the overall performance of the recursive least-squares (RLS) adaptive filter. In this letter, we focus on the data-reuse approach, aiming to improve the convergence rate/tracking of the algorithm by reusing the same set of data (i.e., the input and reference signals) several times. First, we present a computationally efficient data-reuse RLS algorithm, which is the result of a low complexity implementation of the data-reuse process. Moreover, we extend the idea to the fast RLS algorithm. Simulations performed in the context of echo cancellation support the performance gain.
Topics & Concepts
Recursive least squares filterReuseComputer scienceAlgorithmContext (archaeology)Convergence (economics)Rate of convergenceSet (abstract data type)Adaptive filterLeast-squares function approximationProcess (computing)MathematicsKey (lock)StatisticsEngineeringEstimatorWaste managementBiologyEconomicsPaleontologyEconomic growthProgramming languageComputer securityOperating systemAdvanced Adaptive Filtering TechniquesSpeech and Audio ProcessingBlind Source Separation Techniques