From Tutorial on Neural Systems Modeling, Chapter 7:
This tool trains two-layered, feedforward networks of sigmoidal units on pattern association tasks by estimating the network error gradient using parallel weight perturbation, and by updating all network weights simultaneously. This is similar to the one-weight-at-a-time tool pertGradient1By1, except that all weights are perturbed and updated simultaneously. Also the network is not limited to one output unit only.
Researchers should cite this work as follows:
Tutorial on Neural Systems Modeling, Copyright 2010 Sinauer Associates Inc.
Author: Thomas J. Anastasio
AbderRahman N Sobh; Jessica S Johnson; NanoBio Node (2014), "[Illinois]: Error Gradient Estimations Due to Parallel Perturbation of Weights," http://nanohub.org/resources/pertgradll. (DOI: 10.4231/D3SQ8QJ4B).