Approximating Nonlinear Activation Function Using Genetic Programming

Modern advancements in hardware implementation of Deep Neural Networks (DNNs) have underscored the need for efficient and accurate nonlinear activation function approximations to reduce computational complexity in resource-constrained environments like FPGA. Traditional methods face challenges in ac... View More