Abstract: This paper presents a novel VLSI architecture design of the Sigmoid activation function using Chebyshev’s polynomial approximation for efficient hardware realization. The Sigmoid activation ...
Abstract: The activation function is crucial in artificial neural networks for transforming inputs into outputs, introducing nonlinearity necessary for learning intricate patterns and making precise ...
This is an artifact for the tool called WraAct, which over-approximates the function hulls of various activation functions (including leaky ReLU, ReLU, sigmoid, tanh, and maxpool). This artifact ...
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