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Evaluation of Nonlinear Prediction Capability of Neuron Networks for Electrocardiogram
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- Kobayakawa Shunsuke
- Kyushu Institute of Technology Graduate School
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- Fujii Takafumi
- JTEKT Corporation
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- Yokoi Hirokazu
- Kyushu Institute of Technology Graduate School
Bibliographic Information
- Other Title
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- 心電図に対するニューロンネットワークの非線形予測能力の評価(一般講演1A)
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Description
Old drivers on vehicles of cars, trains and airplanes, etc. are increasing in our aged society advancing today. Therefore it's expected that the probability occurred of a serious accident by incapacitation of an old driver will be high. The analytical result of ECG is indispensable as the indicator to stop accidents of this kind from happening. The purpose of this paper is to estimate the model to solve general nonlinear predictability problems taking the case of an ECG. The models to evaluate comparison are a non-recursion type 1st-order Volterra neuron network (N1VNN) and a non-recursion type Volterra neuron network (NVNN) of discrete time. The result is which the NVNN is better than the N1 VNN.
Journal
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- Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association
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Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association 20 (0), 9-12, 2007
Biomedical Fuzzy Systems Association
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Details 詳細情報について
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- CRID
- 1390001205227936896
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- NII Article ID
- 110008136382
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- ISSN
- 24242586
- 13451510
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed