Convex combinations of multiple kernel adaptive filters

Wei Gao; Yi Yan; Lingling Zhang; Qunfei Zhang

doi:10.1109/ICSPCC.2017.8242551

Convex combinations of multiple kernel adaptive filters

Wei Gao, Yi Yan, Lingling Zhang, Qunfei Zhang

School of Marine Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In this paper, we aim to improve the overall performance of kernel adaptive filters by adaptively combining several component filters with different parameters setting in the practical applications. The convex combination scheme is exploited to incorporate any two parallel diversity branches which could be the component filter or the output of previous combination layer. The proposed convex combination of multiple kernel adaptive filters can provide the more robust and better performance than the single filters with fixed parameters especially in the nonstationary complex environments without priori knowledge. Simulation results illustrate the superior performance of the proposed approach.

Original language	English
Title of host publication	2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538631409
DOIs	https://doi.org/10.1109/ICSPCC.2017.8242551
State	Published - 29 Dec 2017
Event	7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017 - Xiamen, Fujian, China Duration: 22 Oct 2017 → 25 Oct 2017

Publication series

Name	2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Volume	2017-January

Conference

Conference	7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Country/Territory	China
City	Xiamen, Fujian
Period	22/10/17 → 25/10/17

Keywords

Convex combination
kernel adaptive filters
nonstationary
robustness

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10.1109/ICSPCC.2017.8242551

Cite this

Gao, W., Yan, Y., Zhang, L., & Zhang, Q. (2017). Convex combinations of multiple kernel adaptive filters. In 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017 (pp. 1-5). (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSPCC.2017.8242551

Gao, Wei ; Yan, Yi ; Zhang, Lingling et al. / Convex combinations of multiple kernel adaptive filters. 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-5 (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017).

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abstract = "In this paper, we aim to improve the overall performance of kernel adaptive filters by adaptively combining several component filters with different parameters setting in the practical applications. The convex combination scheme is exploited to incorporate any two parallel diversity branches which could be the component filter or the output of previous combination layer. The proposed convex combination of multiple kernel adaptive filters can provide the more robust and better performance than the single filters with fixed parameters especially in the nonstationary complex environments without priori knowledge. Simulation results illustrate the superior performance of the proposed approach.",

keywords = "Convex combination, kernel adaptive filters, nonstationary, robustness",

author = "Wei Gao and Yi Yan and Lingling Zhang and Qunfei Zhang",

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year = "2017",

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Gao, W, Yan, Y, Zhang, L & Zhang, Q 2017, Convex combinations of multiple kernel adaptive filters. in 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017, Xiamen, Fujian, China, 22/10/17. https://doi.org/10.1109/ICSPCC.2017.8242551

Convex combinations of multiple kernel adaptive filters. / Gao, Wei; Yan, Yi; Zhang, Lingling et al.
2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-5 (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhang, Lingling

AU - Zhang, Qunfei

PY - 2017/12/29

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N2 - In this paper, we aim to improve the overall performance of kernel adaptive filters by adaptively combining several component filters with different parameters setting in the practical applications. The convex combination scheme is exploited to incorporate any two parallel diversity branches which could be the component filter or the output of previous combination layer. The proposed convex combination of multiple kernel adaptive filters can provide the more robust and better performance than the single filters with fixed parameters especially in the nonstationary complex environments without priori knowledge. Simulation results illustrate the superior performance of the proposed approach.

AB - In this paper, we aim to improve the overall performance of kernel adaptive filters by adaptively combining several component filters with different parameters setting in the practical applications. The convex combination scheme is exploited to incorporate any two parallel diversity branches which could be the component filter or the output of previous combination layer. The proposed convex combination of multiple kernel adaptive filters can provide the more robust and better performance than the single filters with fixed parameters especially in the nonstationary complex environments without priori knowledge. Simulation results illustrate the superior performance of the proposed approach.

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017

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ER -

Gao W, Yan Y, Zhang L, Zhang Q. Convex combinations of multiple kernel adaptive filters. In 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-5. (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017). doi: 10.1109/ICSPCC.2017.8242551

Convex combinations of multiple kernel adaptive filters

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