Mixed Pattern Segmentation by Using Chaotic Neural Networks
スポンサーリンク
概要
- 論文の詳細を見る
Many pattern segmentation systems have been developed by artificial neural networks. Those systems, including the perceptron and the associative memory are capable to map an input to one of the memorized patterns. However, in order to extract plural patterns from a mixed figure at once, we have to embed a specialized mechanism in their systems. The segmentation problem is still one of the difficult problems in image processing and speech recognition. This paper proposes a new pattern segmentation system using chaotic neural network. The proposed system can discriminate several patterns at once, even when they are overlapped each other. Our system is also reconfigurable, because it consists of two simple components: "back-propagation" and "chaotic neuron model" where the combination of two components plays a key role.
- 一般社団法人情報処理学会の論文
- 2001-05-15
著者
-
Takefuji Y
Keio Univ. Kanagawa Jpn
-
Takefuji Yoshiyasu
Faculty Of Environmental Information Keio University
-
FUKUHARA YOSHIHISA
Graduate School of Media and Governance, Keio University
-
Fukuhara Yoshihisa
Graduate School Of Media And Governance Keio University
関連論文
- Mixed Pattern Segmentation by Using Chaotic Neural Networks
- Motion Feature Extraction Using Second-order Neural Network and Self-organizing Map for Gesture Recognition
- Euro Banknote Recognition System Using a Three-layered Perceptron and RBF Networks
- Relation between Brain Activity of fMRI and NIRS image at the Rehabilitation Training
- Motion Feature Extraction Using Second-order Neural Network and Self-organizing Map for Gesture Recognition
- Motion Feature Extraction Using Second-order Neural Network and Self-organizing Map for Gesture Recognition