IEICE TRANSACTIONS on Information
Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map
Summary :
For a kernel-based topographic map formation, kMER (kernel-based maximum entropy learning rule) was proposed by Van Hulle, and some effective learning rules related to kMER have been proposed so far with many applications. However, no discusions have been made concerning the determination of the number of units in kMER. This letter describes a unit-pruning rule, which permits automatic contruction of an appropriate-sized map to acquire the global topographic features underlying the input data. The effectiveness and the validity of the present rule have been confirmed by some preliminary computer simulations.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.3 pp.675-678
- Publication Date
- 2005/03/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.3.675
- Type of Manuscript
- LETTER
- Category
- Biocybernetics, Neurocomputing
Authors
Keyword
Latest Issue
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Eiji UCHINO, Noriaki SUETAKE, Chuhei ISHIGAKI, "Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 3, pp. 675-678, March 2005, doi: 10.1093/ietisy/e88-d.3.675.
Abstract: For a kernel-based topographic map formation, kMER (kernel-based maximum entropy learning rule) was proposed by Van Hulle, and some effective learning rules related to kMER have been proposed so far with many applications. However, no discusions have been made concerning the determination of the number of units in kMER. This letter describes a unit-pruning rule, which permits automatic contruction of an appropriate-sized map to acquire the global topographic features underlying the input data. The effectiveness and the validity of the present rule have been confirmed by some preliminary computer simulations.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.3.675/_p
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@ARTICLE{e88-d_3_675,
author={Eiji UCHINO, Noriaki SUETAKE, Chuhei ISHIGAKI, },
journal={IEICE TRANSACTIONS on Information},
title={Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map},
year={2005},
volume={E88-D},
number={3},
pages={675-678},
abstract={For a kernel-based topographic map formation, kMER (kernel-based maximum entropy learning rule) was proposed by Van Hulle, and some effective learning rules related to kMER have been proposed so far with many applications. However, no discusions have been made concerning the determination of the number of units in kMER. This letter describes a unit-pruning rule, which permits automatic contruction of an appropriate-sized map to acquire the global topographic features underlying the input data. The effectiveness and the validity of the present rule have been confirmed by some preliminary computer simulations.},
keywords={},
doi={10.1093/ietisy/e88-d.3.675},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - Pruning Rule for kMER-Based Acquisition of the Global Topographic Feature Map
T2 - IEICE TRANSACTIONS on Information
SP - 675
EP - 678
AU - Eiji UCHINO
AU - Noriaki SUETAKE
AU - Chuhei ISHIGAKI
PY - 2005
DO - 10.1093/ietisy/e88-d.3.675
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2005
AB - For a kernel-based topographic map formation, kMER (kernel-based maximum entropy learning rule) was proposed by Van Hulle, and some effective learning rules related to kMER have been proposed so far with many applications. However, no discusions have been made concerning the determination of the number of units in kMER. This letter describes a unit-pruning rule, which permits automatic contruction of an appropriate-sized map to acquire the global topographic features underlying the input data. The effectiveness and the validity of the present rule have been confirmed by some preliminary computer simulations.
ER -
English
