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Title: Variable length adaptive filtering within incremental learning algorithms for distributed networks
Authors: Li, Leilei
Zhang, Yonggang
Chambers, Jonathon
Keywords: Variable tap-length
Distributed processing
Adaptive filters
Incremental algorithm
Issue Date: 2008
Publisher: © IEEE
Citation: LI, L., ZHANG, Y. and CHAMBERS, J., 2008. Variable length adaptive filtering within incremental learning algorithms for distributed networks. IN: 42nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 26-29 October, pp. 225-229
Abstract: In this paper we propose the use of variable length adaptive filtering within the context of incremental learning for distributed networks. Algorithms for such incremental learning strategies must have low computational complexity and require minimal communication between nodes as compared to centralized networks. To match the dynamics of the data across the network we optimize the length of the adaptive filters used within each node by exploiting the statistics of the local signals to each node. In particular, we use a fractional tap-length solution to determine the length of the adaptive filter within each node, the coefficients of which are adapted with an incremental-learning learning algorithm. Simulation studies are presented to confirm the convergence properties of the scheme and these are verified by theoretical analysis of excess mean square error and mean square deviation.
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ACSSC.2008.5074397
URI: https://dspace.lboro.ac.uk/2134/5538
ISBN: 9781424429400
ISSN: 1058-6393
Appears in Collections:Conference Papers and Contributions (Electronic, Electrical and Systems Engineering)

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