Abstract
Artificial Neural Networks have a wide application in terms of research areas but they have never really lived up to the promise they seemed to be in the beginning of the 80s. One of the reasons for this is the lack of hardware for their implementation in a straightforward and simple way. This paper presents a tool to respond to this need: An Automatic Neural Generator. The generator allows a user to specify the number of bits used in each part of the neural network and programs the selected FPGA with the network. To measure the accuracy of the implementation an automatically built neural network was inserted in a control loop and compared with Matlab.
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Reis, L., Aguiar, L., Baptista, D., Morgado Dias, F. (2011). ANGE – Automatic Neural Generator. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21738-8_57
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DOI: https://doi.org/10.1007/978-3-642-21738-8_57
Publisher Name: Springer, Berlin, Heidelberg
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