On the Construction of Support Wavelet Network

Junbin Gao; F Chen; D Shi

doi:10.1109/ICSMC.2004.1400833

On the Construction of Support Wavelet Network

Junbin Gao
, F Chen
, D Shi

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

6 Citations (Scopus)

Abstract

Wavelet networks have emerged as a powerful tool for nonparametric estimation. It is a method implementing inverse discrete wavelet transform with coefficient optimization techniques from machine learning field. However, conventional ways to construct wavelet networks are based on empirical risk minimization (ERM) principle, which has been proven not as robust as structural risk minimization (SRM) principle. Thus, to explore the optimal architecture of wavelet networks, we constructed wavelet networks based on SRM principle. This paper describes the kernel-based way to optimize the architecture of wavelet networks. Based on the frame theory, wavelet kernel functions are found. After that, the wavelet network is constructed with support vectors generated by the wavelet kernel functions.

Original language	English
Title of host publication	Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics
Editors	Thissen W, Wieringa P, Pantic M, Ludema M
Place of Publication	Los Alamitos, United States of America
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	3204-3207
Volume	4, 10-13 Oct
ISBN (Print)	0780385675
DOIs	https://doi.org/10.1109/ICSMC.2004.1400833
Publication status	Published - 2004
Event	2004 IEEE International Conference on Systems, Man and Cybernetics - The Hague, Netherlands Duration: 10 Oct 2004 → 13 Oct 2004

Conference

Conference	2004 IEEE International Conference on Systems, Man and Cybernetics
City	The Hague, Netherlands
Period	10/10/04 → 13/10/04

Keywords

Neural, Evolutionary and Fuzzy Computation

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10.1109/ICSMC.2004.1400833

https://hdl.handle.net/1959.11/4596

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title = "On the Construction of Support Wavelet Network",

abstract = "Wavelet networks have emerged as a powerful tool for nonparametric estimation. It is a method implementing inverse discrete wavelet transform with coefficient optimization techniques from machine learning field. However, conventional ways to construct wavelet networks are based on empirical risk minimization (ERM) principle, which has been proven not as robust as structural risk minimization (SRM) principle. Thus, to explore the optimal architecture of wavelet networks, we constructed wavelet networks based on SRM principle. This paper describes the kernel-based way to optimize the architecture of wavelet networks. Based on the frame theory, wavelet kernel functions are found. After that, the wavelet network is constructed with support vectors generated by the wavelet kernel functions.",

keywords = "Neural, Evolutionary and Fuzzy Computation",

author = "Junbin Gao and F Chen and D Shi",

year = "2004",

doi = "10.1109/ICSMC.2004.1400833",

language = "English",

isbn = "0780385675",

volume = "4, 10-13 Oct",

pages = "3204--3207",

editor = "Thissen W and Wieringa P and Pantic M and Ludema M",

booktitle = "Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

note = "2004 IEEE International Conference on Systems, Man and Cybernetics ; Conference date: 10-10-2004 Through 13-10-2004",

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Gao, J, Chen, F & Shi, D 2004, On the Construction of Support Wavelet Network. in T W, W P, P M & L M (eds), Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics. vol. 4, 10-13 Oct, Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, United States of America, pp. 3204-3207, 2004 IEEE International Conference on Systems, Man and Cybernetics, The Hague, Netherlands, 10/10/04. https://doi.org/10.1109/ICSMC.2004.1400833

On the Construction of Support Wavelet Network. / Gao, Junbin; Chen, F; Shi, D.
Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics. ed. / Thissen W; Wieringa P; Pantic M; Ludema M. Vol. 4, 10-13 Oct Los Alamitos, United States of America: Institute of Electrical and Electronics Engineers (IEEE), 2004. p. 3204-3207.

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

TY - GEN

T1 - On the Construction of Support Wavelet Network

AU - Gao, Junbin

AU - Chen, F

AU - Shi, D

PY - 2004

Y1 - 2004

N2 - Wavelet networks have emerged as a powerful tool for nonparametric estimation. It is a method implementing inverse discrete wavelet transform with coefficient optimization techniques from machine learning field. However, conventional ways to construct wavelet networks are based on empirical risk minimization (ERM) principle, which has been proven not as robust as structural risk minimization (SRM) principle. Thus, to explore the optimal architecture of wavelet networks, we constructed wavelet networks based on SRM principle. This paper describes the kernel-based way to optimize the architecture of wavelet networks. Based on the frame theory, wavelet kernel functions are found. After that, the wavelet network is constructed with support vectors generated by the wavelet kernel functions.

AB - Wavelet networks have emerged as a powerful tool for nonparametric estimation. It is a method implementing inverse discrete wavelet transform with coefficient optimization techniques from machine learning field. However, conventional ways to construct wavelet networks are based on empirical risk minimization (ERM) principle, which has been proven not as robust as structural risk minimization (SRM) principle. Thus, to explore the optimal architecture of wavelet networks, we constructed wavelet networks based on SRM principle. This paper describes the kernel-based way to optimize the architecture of wavelet networks. Based on the frame theory, wavelet kernel functions are found. After that, the wavelet network is constructed with support vectors generated by the wavelet kernel functions.

KW - Neural, Evolutionary and Fuzzy Computation

UR - http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=1400833

U2 - 10.1109/ICSMC.2004.1400833

DO - 10.1109/ICSMC.2004.1400833

M3 - Conference contribution

SN - 0780385675

VL - 4, 10-13 Oct

SP - 3204

EP - 3207

BT - Proceedings of 2004 IEEE International Conference on Systems, Man and Cybernetics

A2 - W, Thissen

A2 - P, Wieringa

A2 - M, Pantic

A2 - M, Ludema

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Los Alamitos, United States of America

T2 - 2004 IEEE International Conference on Systems, Man and Cybernetics

Y2 - 10 October 2004 through 13 October 2004

ER -

On the Construction of Support Wavelet Network

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