Effects of varying parameters on properties of self-organizing feature maps
β Scribed by Sungzoon Cho; Min Jang; James A. Reggia
- Publisher
- Springer US
- Year
- 1996
- Tongue
- English
- Weight
- 609 KB
- Volume
- 4
- Category
- Article
- ISSN
- 1370-4621
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
We propose a new scheme for designing a nearest-prototype classi"er using Kohonen's self-organizing feature map (SOFM). The net starts with the minimum number of prototypes which is equal to the number of classes. Then on the basis of the classi"cation performance, new prototypes are generated dynam
A serf-organizing feature map was used for modelling of batch yeast cultures. The model was constructed by training the neural network with experimental data of the specific rates. Estimates of state variables were obtained from the neural network model and differential mass balance equations via in
## Abstract Kohonen's model as the selfβorganizing model for the neural network can be considered as a kind of adaptive vector quantization algorithm. Numerous reports have been presented on the application of the model to practical problems. Although some results have been presented for the theore