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A Fast Converging Partial Update LMS Algorithm with Random Combining Strategy

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Abstract

Partial update (PU) techniques efficiently reduce computational complexity, especially for long-tap applications such as echo cancelation problems. However, periodic signals are known to induce instability for many PU algorithms, but not the stochastic PU (SPU) algorithm. For a small enough step-size, the SPU algorithm guarantees stability. However, it suffers a slow convergence speed. This paper proposes a non-uniformly distributed SPU (NSPU) least-mean-square (LMS) algorithm, which updates the taps in a non-uniform fashion such that a bigger tap gains a higher updating probability. This can be accomplished by randomly combining a “data independent” (SPU) with a “data dependent” (maximum partial output) PU criteria. Our approach not only preserves the stability of the SPU LMS algorithm but also enhances the convergence speed with a lower hardware cost. Simulation results show that our NSPU LMS algorithm demonstrates significant improvements when only one-sixteenths of total taps are updated at each iteration.

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Notes

  1. If \(N=512\), we need to allocate the memory size of about 512G bytes to a floating-point and double-precision matrix \(\mathbf G \)

  2. The baseline means each group is chosen with equal probability. By the word “deemphasize”, we mean the number of counts within one group is below the baseline.

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Acknowledgments

This work was supported in part by the National Science Council, R.O.C., under Grant 101-2218-E-197-001.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Ilan University, I-lan City , 26041, Taiwan, ROC

    Ying-Ren Chien

  2. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung , 80778, Taiwan, ROC

    Shao-I Chu

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  1. Ying-Ren Chien
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  2. Shao-I Chu
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Correspondence to Ying-Ren Chien.

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Chien, YR., Chu, SI. A Fast Converging Partial Update LMS Algorithm with Random Combining Strategy. Circuits Syst Signal Process 33, 1883–1898 (2014). https://doi.org/10.1007/s00034-013-9724-y

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