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A Proportionate NLMS Algorithm for the Identification of Sparse Bilinear Forms | IEEE Conference Publication | IEEE Xplore

A Proportionate NLMS Algorithm for the Identification of Sparse Bilinear Forms


Abstract:

Proportionate-type algorithms are designed to exploit the sparseness character of the systems to be identified, in order to improve the overall convergence of the adaptiv...Show More

Abstract:

Proportionate-type algorithms are designed to exploit the sparseness character of the systems to be identified, in order to improve the overall convergence of the adaptive filters used in this context. However, when the parameter space is large, the system identification problem becomes more challenging. In this paper, we focus on the identification of bilinear forms, where the bilinear term is defined with respect to the impulse responses of a spatiotemporal model. In this framework, we develop a proportionate normalized least-mean-square algorithm tailored for the identification of such bilinear forms. Simulation results indicate the good performance of the proposed algorithm, in terms of both convergence rate and computational complexity.
Date of Conference: 04-06 July 2018
Date Added to IEEE Xplore: 23 August 2018
ISBN Information:
Conference Location: Athens, Greece

References

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