Acceleration of adaptive proximal forward-backward splitting method and its application to sparse system identification

In this paper, we propose an acceleration technique of the adaptive filtering scheme called adaptive proximal forward-backward splitting method. For accelerating the convergence rate, the proposed method includes a step to shift the current estimate in the direction of the difference between the cur...

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Bibliographic Details
Published in:2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 4296 - 4299
Main Authors: Yamagishi, Masao, Yukawa, Masahiro, Yamada, Isao
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2011
Subjects:
Acceleration
Adaptive systems
Convergence
Noise
parallel projection
Projection algorithms
proximal forward-backward splitting method
sparse system identification
Steady-state
variable metric
ISBN:9781457705380, 1457705389
ISSN:1520-6149
Online Access:Get full text
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Summary:In this paper, we propose an acceleration technique of the adaptive filtering scheme called adaptive proximal forward-backward splitting method. For accelerating the convergence rate, the proposed method includes a step to shift the current estimate in the direction of the difference between the current and previous estimates based on the Fast Iterative Shrinkage/Thresholding Algorithm (FISTA). The computational complexity for this additional step is fairly low compared to the overall complexity of the algorithm. As an example of the proposed method, we derive an acceleration of the composition of the Adoptively Weighted Soft-Thresholding (AWST) operator and the exponentially weighted adaptive parallel projection. AWST shrinks the estimated filter coefficients to zero for exploiting the sparsity of the system to be estimated and the exponentially weighted adaptive parallel projection algorithm realizes high accuracy by utilizing all available information at each iteration. This accelerated method improves the steady-state mismatch drastically with its con vergence speed as fast as the proportionate affine projection algorithm.
ISBN:9781457705380
1457705389
ISSN:1520-6149
DOI:10.1109/ICASSP.2011.5947303