基于統計空間映射的自學習模式識別方法

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基于統計空間映射的自學習模式識別方法

徐正光, 瞿壽德, 于連榮

文章導航 > 工程科學學報 > 2003 > 25(5): 480-482

徐正光, 瞿壽德, 于連榮. 基于統計空間映射的自學習模式識別方法[J]. 工程科學學報, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

引用本文:

徐正光, 瞿壽德, 于連榮. 基于統計空間映射的自學習模式識別方法[J]. 工程科學學報, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

XU Zhengguang, QU Shoude, YU Lianrong. Self-Learning Pattern Recognition Method Base on the Statistical Space Mapping[J]. Chinese Journal of Engineering, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

Citation:

XU Zhengguang, QU Shoude, YU Lianrong. Self-Learning Pattern Recognition Method Base on the Statistical Space Mapping[J]. Chinese Journal of Engineering, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

徐正光, 瞿壽德, 于連榮. 基于統計空間映射的自學習模式識別方法[J]. 工程科學學報, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

引用本文:

徐正光, 瞿壽德, 于連榮. 基于統計空間映射的自學習模式識別方法[J]. 工程科學學報, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

XU Zhengguang, QU Shoude, YU Lianrong. Self-Learning Pattern Recognition Method Base on the Statistical Space Mapping[J]. Chinese Journal of Engineering, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

Citation:

XU Zhengguang, QU Shoude, YU Lianrong. Self-Learning Pattern Recognition Method Base on the Statistical Space Mapping[J]. Chinese Journal of Engineering, 2003, 25(5): 480-482. doi: 10.13374/j.issn1001-053x.2003.05.050

基于統計空間映射的自學習模式識別方法

doi: 10.13374/j.issn1001-053x.2003.05.050

1. 北京科技大學信息工程學院, 北京 100083;
2. 河南省工業學校, 鄭州 450002

基金項目:

國家自然科學基金資助課題(No.96213949.1)

作者簡介:
徐正光男,43歲,副教授

中圖分類號: TP274
計量
- 文章訪問數: 160
- HTML全文瀏覽量: 22
- PDF下載量: 8
- 被引次數: 0
出版歷程
- 收稿日期: 2002-11-22
- 網絡出版日期: 2021-08-17

Self-Learning Pattern Recognition Method Base on the Statistical Space Mapping

1. Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China;
2. Industry School of Henan Province, Zhengzhou 450002, China

摘要: 針對生產工況實測數據不能覆蓋整個數據空間的現象,提出了一種基于統計空間映射的自學習模式識別方法.通過實測數據的仿真實驗驗證了該方法的有效性.
- 自學習 /
- 模式識別 /
- 統計空間映射
Abstract: Base on the statistical space mapping a self-learning method was proposed, which can overcome the shortcoming that the measured work-state data can not cover all the data space. Simulating experiment at results for the measured work-state data show its availability.
- self-learning /
- pattern recognition /
- statistical

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文章訪問數: 160
HTML全文瀏覽量: 22
PDF下載量: 8
被引次數: 0

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