Performance Analysis of Shrinkage Linear Complex-Valued LMS Algorithm

Long Shi, Haiquan Zhao, Yuriy Zakharov

Research output: Contribution to journalArticlepeer-review


The shrinkage linear complex-valued least mean squares (SL-CLMS) algorithm with a variable step size overcomes the conflicting issue between fast convergence and low steady-state misalignment. To the best of our knowledge, the theoretical performance analysis of the SL-CLMS algorithm has not been presented yet. This letter focuses on the theoretical analysis of the excess mean square error transient and steady-state performance of the SL-CLMS algorithm. Simulation results obtained for identification scenarios show a good match with the analytical results.
Original languageEnglish
Pages (from-to)1202-1206
Number of pages5
JournalIEEE Signal Processing Letters
Issue number8
Publication statusPublished - 1 Jul 2019

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