Building localized basis function networks using context dependent clustering

Marcin Blachnik; Wodzisaw Duch

doi:10.1007/978-3-540-87536-9_50

Building localized basis function networks using context dependent clustering

Marcin Blachnik
, Wodzisaw Duch

Department of Industrial Informatics (RM/RM4)

Nicolaus Copernicus University in Toruń

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

1 Citation (Scopus)

Abstract

Networks based on basis set function expansions, such as the Radial Basis Function (RBF), or Separable Basis Function (SBF) networks, have non-linear parameters that are not trivial to optimize. Clustering techniques are frequently used to optimize positions of localized functions. Context-dependent fuzzy clustering techniques improve convergence of parameter optimization, leading to better networks and facilitating formulation of prototype-based logical rules that provide low-complexity models of data.

Original language	English
Title of host publication	Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings
Publisher	Springer Verlag
Pages	482-491
Number of pages	10
Edition	PART 1
ISBN (Print)	3540875352, 9783540875352
DOIs	https://doi.org/10.1007/978-3-540-87536-9_50
Publication status	Published - 2008
Event	18th International Conference on Artificial Neural Networks, ICANN 2008 - Prague, Czech Republic Duration: 3 Sept 2008 → 6 Sept 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	5163 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Artificial Neural Networks, ICANN 2008
Country/Territory	Czech Republic
City	Prague
Period	3/09/08 → 6/09/08

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-87536-9_50

Cite this

Blachnik, M., & Duch, W. (2008). Building localized basis function networks using context dependent clustering. In Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings (PART 1 ed., pp. 482-491). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5163 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-87536-9_50

Blachnik, Marcin ; Duch, Wodzisaw. / Building localized basis function networks using context dependent clustering. Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1. ed. Springer Verlag, 2008. pp. 482-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{7be6f416ede94df388f839e4cf20196d,

title = "Building localized basis function networks using context dependent clustering",

abstract = "Networks based on basis set function expansions, such as the Radial Basis Function (RBF), or Separable Basis Function (SBF) networks, have non-linear parameters that are not trivial to optimize. Clustering techniques are frequently used to optimize positions of localized functions. Context-dependent fuzzy clustering techniques improve convergence of parameter optimization, leading to better networks and facilitating formulation of prototype-based logical rules that provide low-complexity models of data.",

author = "Marcin Blachnik and Wodzisaw Duch",

year = "2008",

doi = "10.1007/978-3-540-87536-9\_50",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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pages = "482--491",

booktitle = "Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings",

address = "Germany",

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note = "18th International Conference on Artificial Neural Networks, ICANN 2008 ; Conference date: 03-09-2008 Through 06-09-2008",

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Blachnik, M & Duch, W 2008, Building localized basis function networks using context dependent clustering. in Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5163 LNCS, Springer Verlag, pp. 482-491, 18th International Conference on Artificial Neural Networks, ICANN 2008, Prague, Czech Republic, 3/09/08. https://doi.org/10.1007/978-3-540-87536-9_50

Building localized basis function networks using context dependent clustering. / Blachnik, Marcin; Duch, Wodzisaw.
Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1. ed. Springer Verlag, 2008. p. 482-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5163 LNCS, No. PART 1).

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

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AB - Networks based on basis set function expansions, such as the Radial Basis Function (RBF), or Separable Basis Function (SBF) networks, have non-linear parameters that are not trivial to optimize. Clustering techniques are frequently used to optimize positions of localized functions. Context-dependent fuzzy clustering techniques improve convergence of parameter optimization, leading to better networks and facilitating formulation of prototype-based logical rules that provide low-complexity models of data.

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SN - 9783540875352

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Blachnik M, Duch W. Building localized basis function networks using context dependent clustering. In Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1 ed. Springer Verlag. 2008. p. 482-491. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-87536-9_50

Building localized basis function networks using context dependent clustering

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