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Disambiguation of "Fraser, Nicholas J."

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A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology.

, , , , , and . ACM Trans. Reconfigurable Technol. Syst., 10 (1): 5:1-5:22 (2016)

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J. K\"astner

J. Schwarz

J. K\"astner

J Walter

J. Vogel

 

Other publications of authors with the same name

A fully pipelined kernel normalised least mean squares processor for accelerated parameter optimisation., , , , , and . FPL, page 1-6. IEEE, (2015)SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks., , , and . CVPR, page 4300-4309. IEEE Computer Society, (2018)Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic., , , , , , and . ICCD, page 419-422. IEEE Computer Society, (2017)FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks., , , , , , , and . ACM Trans. Reconfigurable Technol. Syst., 11 (3): 16:1-16:23 (2018)An FPGA-based spectral anomaly detection system., , , and . FPT, page 175-182. IEEE, (2014)FINN: A Framework for Fast, Scalable Binarized Neural Network Inference., , , , , , and . CoRR, (2016)A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology., , , , , and . ACM Trans. Reconfigurable Technol. Syst., 10 (1): 5:1-5:22 (2016)Braiding: A scheme for resolving hazards in kernel adaptive filters., , , and . FPT, page 136-143. IEEE, (2015)Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic., , , , , , and . CoRR, (2018)FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks., , , , , and . CoRR, (2018)