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On the Regularization of the Memory-Improved Proportionate Affine Projection Algorithm

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Abstract

In order to improve the performance of the conventional algorithms used for network and acoustic echo cancellation, we can exploit the sparseness character of the echo paths (i.e., a small percentage of the impulse response components have a significant magnitude while the rest are zero or small). In this paper, we consider the memory-improved proportionate affine projection algorithm (MIPAPA), which represents an appealing choice for echo cancellation. In this context, we focus on the regularization of this algorithm, relating the regularization parameter to the signal-to-noise ratio. In this way, the algorithm can operate properly in different noisy conditions. Simulation results indicate the good performance of the proposed solution.

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Correspondence to Constantin Paleologu .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Mihăescu, R., Stanciu, C., Paleologu, C. (2018). On the Regularization of the Memory-Improved Proportionate Affine Projection Algorithm. In: Fratu, O., Militaru, N., Halunga, S. (eds) Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-92213-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-92213-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92212-6

  • Online ISBN: 978-3-319-92213-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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