In system identification applications of neural networks, the aim is usually to obtain a dynamically valid model of the system which can be used for system analysis and for controller design. In the present study, a cell to a cell mapping procedure is adopted for the global analysis of non-linear sy
โฆ LIBER โฆ
On the statistical physics of radial basis function networks
โ Scribed by Sean B. Holden; Mahesan Niranjan
- Publisher
- Springer US
- Year
- 1995
- Tongue
- English
- Weight
- 271 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1370-4621
No coin nor oath required. For personal study only.
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An approach./or the implenwntation ql'the Radial Basis Function (RBF) technique is presented and applied to a network qlthe appropriate architecture. TIw paper evplores a melhodohlgy /br selecting kernel fimction parameters and tlw t:~tent to which the mtmber ~?/ RBF mules can be reduced without sig