Distributed global optimization (DGO)

A new technique of global optimization and its applications in particular to neural networks are presented. The algorithm is also compared to other global optimization algorithms such as the gradient descent method, Monte Carlo method, genetic algorithm and other commercial packages. This new optimization technique proved itself worthy of further study after observing its accuracy of convergence, speed of convergence and ease of use. Some of the advantages of this new optimization technique are given.