This work is an organized review on the representational capabilities of artificial neural networks and the questions that arise in their implementation. It covers the Kolmogorov's superposition theorem and different statements regarding how it could be related to the representational power of neura
Effect of signal noise on the learning capability of an artificial neural network
โ Scribed by J.J. Vega; R. Reynoso; H. Carrillo Calvet
- Publisher
- Elsevier Science
- Year
- 2009
- Tongue
- English
- Weight
- 919 KB
- Volume
- 606
- Category
- Article
- ISSN
- 0168-9002
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