FPGA Implementations of Neural Networks
نویسندگان
چکیده
This introductory chapter reviews the basics of artificial-neural-network theory, discusses various aspects of the hardware implementation of neural networks (in both ASIC and FPGA technologies, with a focus on special features of artificial neural networks), and concludes with a brief note on performanceevaluation. Special points are the exploitation of the parallelism inherent in neural networks and the appropriate implementation of arithmetic functions, especially the sigmoid function. With respect to the sigmoid function, the chapter includes a significant contribution.
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FPGA Implementations of Neural Networks - A Survey of a Decade of Progress
The first 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.
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