APA (7th ed.) Citation

Yang, C., Wang, Y., Wang, X., & Geng, L. (2019). WRA: A 2.2-to-6.3 TOPS Highly Unified Dynamically Reconfigurable Accelerator Using a Novel Winograd Decomposition Algorithm for Convolutional Neural Networks. IEEE transactions on circuits and systems. I, Regular papers, 66(9), 3480-3493. https://doi.org/10.1109/TCSI.2019.2928682

Chicago Style (17th ed.) Citation

Yang, Chen, Yizhou Wang, Xiaoli Wang, and Li Geng. "WRA: A 2.2-to-6.3 TOPS Highly Unified Dynamically Reconfigurable Accelerator Using a Novel Winograd Decomposition Algorithm for Convolutional Neural Networks." IEEE Transactions on Circuits and Systems. I, Regular Papers 66, no. 9 (2019): 3480-3493. https://doi.org/10.1109/TCSI.2019.2928682.

MLA (9th ed.) Citation

Yang, Chen, et al. "WRA: A 2.2-to-6.3 TOPS Highly Unified Dynamically Reconfigurable Accelerator Using a Novel Winograd Decomposition Algorithm for Convolutional Neural Networks." IEEE Transactions on Circuits and Systems. I, Regular Papers, vol. 66, no. 9, 2019, pp. 3480-3493, https://doi.org/10.1109/TCSI.2019.2928682.