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

Katedra Informatyki Przemysłowej (RM/RM4)

Nicolaus Copernicus University in Toruń

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

1 Cytowanie z bazy Scopus

Abstrakt

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.

Język oryginału	angielski
Tytuł publikacji goszczącej	Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings
Wydawca	Springer Verlag
Strony	482-491
Liczba stron	10
Edycja	PART 1
ISBN (drukowany)	3540875352, 9783540875352
Identyfikatory DOI	https://doi.org/10.1007/978-3-540-87536-9_50
Status publikacji	Opublikowano - 2008
Wydarzenie	18th International Conference on Artificial Neural Networks, ICANN 2008 - Prague, Republika Czeska Czas trwania: 3 wrz 2008 → 6 wrz 2008

Seria publikacji

Nazwa	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Numer	PART 1
Tom	5163 LNCS
ISSN (drukowany)	0302-9743
ISSN (elektroniczny)	1611-3349

Konferencja

Konferencja	18th International Conference on Artificial Neural Networks, ICANN 2008
Kraj/Terytorium	Republika Czeska
Miejscowość	Prague
Okres	3/09/08 → 6/09/08

Obszary tematyczne ASJC Scopus

Informatyka teoretyczna
Informatyka ogólna

Uzyskaj dostęp do dokumentu

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

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Blachnik, M., & Duch, W. (2008). Building localized basis function networks using context dependent clustering. W Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings (PART 1 red., str. 482-491). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 5163 LNCS, Nr 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. red. Springer Verlag, 2008. str. 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",

language = "English",

isbn = "3540875352",

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

publisher = "Springer Verlag",

number = "PART 1",

pages = "482--491",

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

address = "Germany",

edition = "PART 1",

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. w Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1 wyd., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), nr PART 1, tom 5163 LNCS, Springer Verlag, str. 482-491, 18th International Conference on Artificial Neural Networks, ICANN 2008, Prague, Republika Czeska, 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. red. Springer Verlag, 2008. str. 482-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 5163 LNCS, Nr PART 1).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

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AU - Blachnik, Marcin

AU - Duch, Wodzisaw

PY - 2008

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N2 - 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.

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.

UR - https://www.scopus.com/pages/publications/58849110798

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

M3 - Conference contribution

AN - SCOPUS:58849110798

SN - 3540875352

SN - 9783540875352

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

SP - 482

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BT - Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings

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T2 - 18th International Conference on Artificial Neural Networks, ICANN 2008

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ER -

Blachnik M, Duch W. Building localized basis function networks using context dependent clustering. W Artificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings. PART 1 red. Springer Verlag. 2008. str. 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

Abstrakt

Seria publikacji

Konferencja

Obszary tematyczne ASJC Scopus

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Inne pliki i linki

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Cytowanie