title: A new back-propagation algorithm with coupled neuron.
abstract: A novel neuron model and its learning algorithm are presented. They provide a novel approach for speeding up convergence in the learning of layered neural networks and for training networks of neurons with a nondifferentiable output function by using the gradient descent method. The neuron is called a saturating linear coupled neuron (sl-CONE). From simulation results, it is shown that the sl-CONE has a high convergence rate in learning compared with the conventional backpropagation algorithm.
authors.affiliation: Dept. of Inf. Sci. and Intelligent Syst., Tokushima Univ.
authors.forename: M
authors.initials: M
authors.lastname: Fukumi
authors.forename: S
authors.initials: S
authors.lastname: Omatu