Universal Learning Network Theory

Abstract

In this papaer, Universal Learning Network(U.L.N.) is proposed, which can be used as a fundamntal tool in modeling and control of large-scale complicated systems such as economic, social and living systems as well as industrial plants.
The basic idea of U.L.N. is that most of the large scale complicated systems can be modeled by the network which consists of nonlinearly operated nodes and branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed as ordinary first order difference equations with one sampling time delay.
In this sense, U.L.N. is a natural extention of recurrent neural network. It is also shown from simulation results of nonlinear identification that U.L.N. with arbitrary time delays can model nonlinear systems more efficiently than recurrent neural network.