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A Finite Precision LMS Algorithm for Increased Quantization Robustness
Ansvarig organisation
2003 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat) Published
Abstract [en]

The well known Least Mean Square (LMS) algorithm, or variations thereof are frequently used in adaptive systems. When the LMS algorithm is implemented in a finite precision environment it suffers from quantization effects. These effects can severely degrade the performance of the algorithm. This paper proposes a modification of the LMS algorithm that reduces the impact of quantization at virtually no extra computational cost. The paper contains an off-line evaluation of a system identification scheme where the presented algorithm outperforms the classical LMS algorithm yielding a better modelling of the unknown plant. This approach is well suited for adaptive system identification, e.g. beam-forming, electrocardiography, and echo cancelling.

Ort, förlag, år, upplaga, sidor
Bangkok,: Institute of Electrical and Electronics Engineers Inc. , 2003.
Nyckelord [en]
Digital signal processing, Robustness (control systems), Vectors, Algorithms
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:bth-9895Lokalt ID: oai:bth.se:forskinfo74FDB450B9C932AFC1256C6A0040CC32OAI: oai:DiVA.org:bth-9895DiVA, id: diva2:837874
Konferens
IEEE International Symposium on Circuits and Systems
Tillgänglig från: 2012-09-18 Skapad: 2002-11-07 Senast uppdaterad: 2015-06-30Bibliografiskt granskad

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Dahl, MattiasClaesson, Ingvar

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Dahl, MattiasClaesson, Ingvar
Signalbehandling

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