An optimal dimension expansion procedure for obtaining linearly separable subsets

Yuen-Hsien Tseng*, Ja Ling Wu

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

The authors study the necessary and sufficient condition for linearly separable subsets and then propose an optimal dimension expansion procedure that makes any mapping to be performed by perceptrons learnable by an error-correction procedure. For n-bit parity check problems, it is shown that only one additional dimension is augmented to make them solvable by single-layer perceptrons. Other applications such as for decoding error-correcting codes are also considered.

原文英語
主出版物標題91 IEEE Int Jt Conf Neural Networks IJCNN 91
發行者Publ by IEEE
頁面2461-2465
頁數5
ISBN(列印)0780302273
出版狀態已發佈 - 1991 十二月 1
事件1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
持續時間: 1991 十一月 181991 十一月 21

出版系列

名字91 IEEE Int Jt Conf Neural Networks IJCNN 91

其他

其他1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
城市Singapore, Singapore
期間1991/11/181991/11/21

ASJC Scopus subject areas

  • 工程 (全部)

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