Induced weights artificial neural network

Slawomir Golak

doi:10.1007/11550907_47

Induced weights artificial neural network

Slawomir Golak

Department of Industrial Informatics (RM/RM4)

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

2 Citations (Scopus)

Abstract

It is widely believed in the pattern recognition field that the number of examples needed to achieve an acceptable level of generalization ability depends on the number of independent parameters needed to specify the network configuration. The paper presents a neural network for classification of highdimensional patterns. The network architecture proposed here uses a layer which extracts the global features of patterns. The layer contains neurons whose weights are induced by a neural subnetwork. The method reduces the number of independent parameters describing the layer to the parameters describing the inducing subnetwork.

Original language	English
Title of host publication	Artificial Neural Networks
Subtitle of host publication	Formal Models and Their Applications - ICANN 2005 - 15th International Conference Proceedings
Publisher	Springer Verlag
Pages	295-300
Number of pages	6
ISBN (Print)	3540287558, 9783540287551
DOIs	https://doi.org/10.1007/11550907_47
Publication status	Published - 2005
Event	15th International Conference on Artificial Neural Networks, ICANN 2005 - Warsaw, Poland Duration: 11 Sept 2005 → 15 Sept 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3697 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th International Conference on Artificial Neural Networks, ICANN 2005
Country/Territory	Poland
City	Warsaw
Period	11/09/05 → 15/09/05

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/11550907_47

Cite this

Golak, S. (2005). Induced weights artificial neural network. In Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005 - 15th International Conference Proceedings (pp. 295-300). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3697 LNCS). Springer Verlag. https://doi.org/10.1007/11550907_47

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title = "Induced weights artificial neural network",

abstract = "It is widely believed in the pattern recognition field that the number of examples needed to achieve an acceptable level of generalization ability depends on the number of independent parameters needed to specify the network configuration. The paper presents a neural network for classification of highdimensional patterns. The network architecture proposed here uses a layer which extracts the global features of patterns. The layer contains neurons whose weights are induced by a neural subnetwork. The method reduces the number of independent parameters describing the layer to the parameters describing the inducing subnetwork.",

author = "Slawomir Golak",

year = "2005",

doi = "10.1007/11550907\_47",

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isbn = "3540287558",

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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booktitle = "Artificial Neural Networks",

address = "Germany",

note = "15th International Conference on Artificial Neural Networks, ICANN 2005 ; Conference date: 11-09-2005 Through 15-09-2005",

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Golak, S 2005, Induced weights artificial neural network. in Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005 - 15th International Conference Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3697 LNCS, Springer Verlag, pp. 295-300, 15th International Conference on Artificial Neural Networks, ICANN 2005 , Warsaw, Poland, 11/09/05. https://doi.org/10.1007/11550907_47

Induced weights artificial neural network. / Golak, Slawomir.
Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005 - 15th International Conference Proceedings. Springer Verlag, 2005. p. 295-300 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3697 LNCS).

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

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AB - It is widely believed in the pattern recognition field that the number of examples needed to achieve an acceptable level of generalization ability depends on the number of independent parameters needed to specify the network configuration. The paper presents a neural network for classification of highdimensional patterns. The network architecture proposed here uses a layer which extracts the global features of patterns. The layer contains neurons whose weights are induced by a neural subnetwork. The method reduces the number of independent parameters describing the layer to the parameters describing the inducing subnetwork.

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M3 - Conference contribution

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Golak S. Induced weights artificial neural network. In Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005 - 15th International Conference Proceedings. Springer Verlag. 2005. p. 295-300. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11550907_47

Induced weights artificial neural network

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