access icon free Leaky least mean fourth adaptive algorithm

© The Institution of Engineering and Technology
Received 15/10/2011, Accepted 27/01/2013, Revised 17/10/2012, Published

In this work, a leakage-based variant of the least mean fourth (LMF) algorithm, the leaky least mean fourth (LLMF) algorithm, is proposed. This algorithm will help mitigate the weight drift problem experienced in the conventional LMF algorithm. The main aim of this work is to derive the LLMF adaptive algorithm, analyse its convergence behaviour, and examine its performance in different noise environments. Furthermore, the tracking and transient analysis of the proposed LLMF algorithm are carried out using the energy-conservation relation framework. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and show improved performance obtained through the use of LLMF over the conventional LMF algorithm in a weight drift scenario.

Inspec keywords: least mean squares methods; adaptive filters

Other keywords: energy-conservation relation; transient analysis; leaky least mean fourth adaptive algorithm; weight drift problem; leakage-based variant; noise environment; LLMF adaptive algorithm; tracking analysis; convergence behaviour

Subjects: Filtering methods in signal processing; Interpolation and function approximation (numerical analysis); Signal processing theory; Interpolation and function approximation (numerical analysis)

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