<title>High-order neural network employing adaptive architecture</title>

Abstract

For the two category classification problem a method of creating an adaptive architecture network (AANET) is presented and discussed. The principal means of adaptation of this network is the modification of its architecture. AANET is constructed using the repeated application of the outer product expansion, the Karhunen-Loeve expansion, and the Ho- Kashyap algorithm. A multilayer AANET may then be transformed into an equivalent single layer network by passing a vector x having symbolic terms through the network.