Abstract
The ferst successful FPGA implementation [1] of artificial neural networks (ANNs) was published a little over a decade ago. It is timely to review the progress that has been made in this research area. This brief survey provides a taxonomy for classifying FPGA implementations of ANNs. Different implementation techniques and design issues are discussed. Future research trends are also presented. © Springer-Verlag Berlin Heidelberg 2003.
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CITATION STYLE
Zhu, J., & Sutton, P. (2003). FPGA implementations of neural networks - A survey of a decade of progress. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. https://doi.org/10.1007/978-3-540-45234-8_120
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