Abstract
In this paper, an FPGA hardware implementation based on a recurrent neural network was proposed to compute the distance between a point and an ellipsoid. This implementation takes the 0–1 constraint box into consideration as well, it is also capable to solve the hyperellipsoid problem based on the methodology of an automatic generation of neural hardware tool. The hardware design is based on the Xilinx’s System Generator development tool and experimental results show that the proposed hardware implementation method is very efficient with a high degree of parallelism.
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Acknowledgments
The work described in the paper was supported by the National Science Foundation of China under Grant 61503233.
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Gu, S., Wang, X. (2017). FPGA Implementation of the Projection Based Recurrent Neural Network Approach to Compute the Distance Between a Point and an Ellipsoid. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10639. Springer, Cham. https://doi.org/10.1007/978-3-319-70136-3_19
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DOI: https://doi.org/10.1007/978-3-319-70136-3_19
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