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A Note on Robust Adaptive Volterra Filtering Based on Parallel Subgradient Projection Techniques
Isao YAMADA Takuya OKADA Kohichi SAKANIWA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2003/08/01
Print ISSN: 0916-8508
Type of Manuscript: Special Section LETTER (Special Section on Digital Signal Processing)
nonlinear identification, adaptive filtering, second order Volterra system, parallel subgradient projection,
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A robust adaptive filtering algorithm was established recently (I. Yamada, K. Slavakis, K. Yamada 2002) based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. In this letter, we show the potential applicability of the adaptive algorithm to the identification problem for the second order Volterra systems. The numerical examples demonstrate that a straightforward application of the algorithm to the problem soundly realizes fast and stable convergence for highly colored excited speech like input signals in possibly noisy environments.