Natural Learning of Neural Networks by Reconfiguration

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Spaanenburg, L. and Alberts, R. and Slump, C.H. and Zwaag, B.J. van der (2003) Natural Learning of Neural Networks by Reconfiguration. In: Bioengineered and Bioinspired Systems. Proceedings of SPIE, 5119 . SPIE, pp. 273-284.

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Abstract:The communicational and computational demands of neural networks are hard to satisfy in a digital technology. Temporal computing addresses this problem by iteration, but leaves a slow network. Spatial computing only became an option with the coming of modern FPGA devices. The paper provides two examples. First the balance between area and time is discussed on the realization of a modular feed-forward network. Second, the design of real-time image processing through a Cellular Neural Network is treated. In both examples, reconfiguration can be applied to provide for a natural and transparent support of learning.
Item Type:Book Section
Copyright:© 2003 SPIE
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Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/45308
Official URL:http://dx.doi.org/10.1117/12.499549
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