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- W3146573100 abstract "This paper focuses on numerical function generators (NFGs) based on k-th order polynomial approximations. We show that increasing the polynomial order k reduces significantly the NFG's memory size. However, larger k requires more logic elements and multipliers. To quantify this tradeoff, we introduce the FPGA utilization measure, and then determine the optimum polynomial order k. Experimental results show that: 1) for low accuracies (up to 17 bits), 1st order polynomial approximations produce the most efficient implementations; and 2) for higher accuracies (18 to 24 bits), 2nd-order polynomial approximations produce the most efficient implementations." @default.
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- W3146573100 date "2007-08-01" @default.
- W3146573100 modified "2023-10-16" @default.
- W3146573100 title "Design Method for Numerical Function Generators Based on Polynomial Approximation for FPGA Implementation" @default.
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- W3146573100 doi "https://doi.org/10.1109/dsd.2007.4341481" @default.
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