Rashad A. Al-Jawfi*
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700
Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the activation function is important when… More >
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