A pattern recognition neural network using many sets of weights and biases

Dung Le, Makoto Mizukawa

研究成果: Conference contribution

4 引用 (Scopus)

抜粋

In supervised training, we often try to find out a set of weights and biases for a pattern recognition neural network in order to classify all patterns in a training data set. However, it would be difficult if the neural network was not big enough for learning a large training data set. In this paper, we propose a training method and a design of pattern recognition neural network that is not big but still able to classify all the training patterns exactly. The neural network is designed with a reject output to separate the training data set into some parts for classifying more easily. The training method helps the neural network to find out not only one but many sets of weights and biases for classifying all the training patterns, controlling the recognizing rejection and reducing the error rate. On the other hand, with this design we can reduce the size of the neural network implemented on a FPGA chip in order to make fast smart sensors for the robots.

元の言語English
ホスト出版物のタイトルProceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007
ページ285-290
ページ数6
DOI
出版物ステータスPublished - 2007 10 9
イベント2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007 - Jacksonville, FL, United States
継続期間: 2007 6 202007 6 23

出版物シリーズ

名前Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007

Conference

Conference2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007
United States
Jacksonville, FL
期間07/6/2007/6/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • これを引用

    Le, D., & Mizukawa, M. (2007). A pattern recognition neural network using many sets of weights and biases. : Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007 (pp. 285-290). [4269856] (Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007). https://doi.org/10.1109/CIRA.2007.382856