| Title |
A Self Creating and Organizing Neural Network |
| Keywords |
경쟁학습 ; 신경회로망 ; 자기구조화 ; 적응벡터양자화 ; 신경벡터양자화 Competitive learning ; Neural network ; Self-Organizing ; Adaptive Vector Quantization ; Neural Vector Quantization |
| Abstract |
The Self Creating and Organizing (SCO) is a new architecture and one of the unsupervized learning algorithm for the artificial neural network. SCO begins with only one output node which has a sufficiently wide response range, and the response ranges of all the nodes decrease automatically whether adapting the weights of existing node or creating a new node. It is compared to the Kohonen's Self Organizing Feature Map (SOFM). The results show that SCONN has lots of advantages over other competitive learning architecture. |