A low-complexity RLS-DCD algorithm for volterra system identification
| Autor: | Vitor H. Nascimento, Yuriy Zakharov, Raffaello Claser |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Recursive least squares filter
Average-case complexity Computational complexity theory Computer science System identification 020206 networking & telecommunications 02 engineering and technology 01 natural sciences Adaptive filter Rate of convergence 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Asymptotic computational complexity Probabilistic analysis of algorithms Affine transformation Coordinate descent 010301 acoustics Algorithm |
| Zdroj: | EUSIPCO |
| DOI: | 10.1109/eusipco.2016.7760199 |
| Popis: | Adaptive filters for Volterra system identification must deal with two difficulties: large filter length M (resulting in high computational complexity and low convergence rate) and high correlation in the input sequence. The second problem is minimized by using the recursive least-squares algorithm (RLS), however, its large computation complexity (O(M2)) might be prohibitive in some applications. We propose here a low-complexity RLS algorithm, based on the dichotomous coordinate descent algorithm (DCD), showing that in some situations the computational complexity is reduced to O(M). The new algorithm is compared to the standard RLS, normalized least-mean squares (NLMS) and affine projections (AP) algorithms. |
| Databáze: | OpenAIRE |
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