Molding the Knowledge in Modular Neural Networks


Spaanenburg, L. and Achterop, S. and Slump, C.H. and Zwaag, B.J. van der (2002) Molding the Knowledge in Modular Neural Networks. In: Lerende Oplossingen. Technologiestichting STW, Nijmegen, The Netherlands, pp. 25-26.

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Abstract:Problem description. The learning of monolithic neural networks becomes harder with growing network size. Likewise the knowledge obtained while learning becomes harder to extract. Such disadvantages are caused by a lack of internal structure, that by its presence would reduce the degrees of freedom in evolving to a training target. A suitable internal structure with respect to modular network construction as well as to nodal discrimination is required. Details on the grouping and selection of nodes can sometimes be concluded from the characteristics of the application area; otherwise a comprehensive search within the solution space is necessary.
Item Type:Book Section
Additional information:030.02
Copyright:©STW Technology Foundation
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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