Abstract
Artificial Neural Networks (ANNs) are successfully applied to a variety of data classification and recognition problems. Through experimentation and simulation, acceptable solutions to such problems can be obtained using ANNs. However, the effectiveness of an ANN algorithm strongly depends on the hardware that executes it. This hardware has to capture the inherent parallelism of the ANNs and tolerate the ANN’s need of massive numbers of computations.
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Rehan, S.E., Elmasry, M.I. (1994). A Sampled-Data CMOS VLSI Implementation of a Multi-Character ANN Recognition System. In: Elmasry, M.I. (eds) VLSI Artificial Neural Networks Engineering. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2766-4_2
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DOI: https://doi.org/10.1007/978-1-4615-2766-4_2
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