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Issue No.03 - May/June (2002 vol.22)
pp: 32-40
ABSTRACT
<p>Execution of artificial neural networks, especially for online pattern recognition, mainly depends on time-efficient execution of weighted sums. A new architecture achieves this goal, with a computation time superior to the time complexity of sequential von neumann machines. This architecture uses additional logic to extend the functionality of conventional ram. The authors discuss an implementation of this architecture that uses reconfigurable logic.</p>
CITATION
Jürgen Büddefeld, Karl E. Grosspietsch, "Intelligent-Memory Architecture for Artificial Neural Networks", IEEE Micro, vol.22, no. 3, pp. 32-40, May/June 2002, doi:10.1109/MM.2002.1013302
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