Abstract
Artificial Neural Networks (ANNs) are generally modeled and used as software based. Software models are insufficient in real time applications where ANN output needs to be calculated. ANN has an architecture that can operate in parallel to calculate hidden layers. The fact that ANN has such an architecture makes it potentially fast in calculating certain transactions. However, the speed of these operations in real-time systems depends on the specification of the hardware. Therefore, ANN design has been realized on FPGA which is capable of parallel processing. In this way, the ANN structure was realized in a hardware structure and it was provided to be used on real-time structures.
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Ersoy, M., Kumral, C.D. (2020). Realization of Artificial Neural Networks on FPGA. In: Hemanth, D., Kose, U. (eds) Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-36178-5_31
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DOI: https://doi.org/10.1007/978-3-030-36178-5_31
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