Justification of a neuron-adaptive activation function
Shuxiang Xu, Ming Zhang · 2000
An empirical justification of a neuron-adaptive activation function for feedforward neural networks has been proposed in this paper. Simulation results reveal that feedforward neural networks with the proposed neuron-adaptive activation function present several advantages over traditional neuron-fixed feedforward networks such as increased flexibility, much reduced network size, faster learning, and lessened approximation errors.