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Online Sparse Volterra System Identification Using Projections onto Weighted l(1) Balls

Title
Online Sparse Volterra System Identification Using Projections onto Weighted l(1) Balls
Author
장준혁
Keywords
adaptive filtering; sparse Volterra systems; identification; projections
Issue Date
2013-10
Publisher
IEICE
Citation
IEICE Transactions on Fundamentals of Electronics Communication and Computer Science, 2013, E96A(10), P.1980-1983
Abstract
In this paper, online sparse Volterra system identification is proposed. For that purpose, the conventional adaptive projection-based algorithm with weighted l(1) balls (APWL1) is revisited for nonlinear system identification, whereby the linear-in-parameters nature of Volterra systems is utilized. Compared with sparsity-aware recursive least squares (RLS) based algorithms, requiring higher computational complexity and showing faster convergence and lower steady-state error due to their long memory in time-invariant cases, the proposed approach yields better tracking capability in time-varying cases due to short-term data dependence in updating the weight. Also, when N is the number of sparse Volterra kernels and q is the number of input vectors involved to update the weight, the proposed algorithm requires O(qN) multiplication complexity and O(N log(2) N) sorting-operation complexity. Furthermore, sparsity-aware least mean-squares and affine projection based algorithms are also tested.
URI
https://www.jstage.jst.go.jp/article/transfun/E96.A/10/E96.A_1980/_article
ISSN
0916-8508; 1745-1337
DOI
10.1587/transfun.E96.A.1980
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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