Structured backpropagation network

A novel structured backpropagation network is described. It is different from the classic network as it requires prior knowledge of the problems that the network is dealing with by constructing an appropriate structure to match the problem. This approach can reduce training time and minimize the convergent problems that exist in the classic approaches. This new hybrid network architecture is superior to the traditional approach as this approach is extremely adaptable and expandable to allow the incorporation of mixed network types such as Hopfield, Boltzmann, and backpropagation. To illustrate how this structure network operates, an example in power control systems is shown