The use of a self-organizing neural network as a vector quantizer in the case of a nonstationary lattice is considered. The nonstationarity is handled by expanding the time-dependent parameters of the lattice into a suitable base. Several experimental results are presented concerning the behaviour o
โฆ LIBER โฆ
On quantization error of self-organizing map network
โ Scribed by Yi Sun
- Book ID
- 114295699
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 299 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0925-2312
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A new model for generalized fuzzy inference neural networks (GFINN) is proposed in this paper. The networks consist of three layers: an input-output layer, an if layer, and a then layer. In each layer, there are the operational nodes. A GFINN can perform three representative fuzzy inference methods