4.6 Article

Very High Accuracy Hyperbolic Tangent Function Implementation in FPGAs

Journal

IEEE ACCESS
Volume 11, Issue -, Pages 23701-23713

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2023.3253668

Keywords

Field programmable gate arrays; Chebyshev approximation; Artificial neural networks; Table lookup; Matlab; Interpolation; Activation function; artificial neural network; FPGA

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The paper presents a relatively simple method for implementing the hyperbolic tangent function on FPGAs using ordinary or Chebyshev polynomials. Various implementation versions with different polynomial degrees and intervals have been considered for both floating-point and fixed-point computations. The proposed method achieves high accuracy while maintaining reasonable resource utilization and calculation time. It can serve as an effective alternative to other methods like CORDIC and can be easily adapted for implementing other mathematical functions.
The paper presents in detail a relatively simple implementation method of the hyperbolic tangent function, particularly targeted for FPGAs. The research goal of the proposed method was to examine the usage of the approximation of ordinary or Chebyshev polynomials for the implementation of the function. Several miscellaneous implementation versions have been considered. They differ in the polynomial degree, number of intervals for which the domain of the function is divided, etc. Both floating-point and fixed-point implementations have been presented. An impact on the FPGA resources utilization and calculations time for the implementation versions has also been briefly analyzed. Special attention has been paid to the accuracy of the calculations of the function. It turned out that applying the proposed method, a very high calculations accuracy can be achieved, while simultaneously maintaining reasonable resources utilization and short calculations time. The proposed method can be an effective alternative to other encountered implementation methods such as CORDIC. Additionally, the presented hardware architecture is more versatile and can be easily adapted for the implementation of other mathematical functions.

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