Why a window-based learning algorithm using an Effective Boltzmann machine is superior to the original BM learning algorithm

Many pattern recognition problems are viewed as problems that can be solved using a window based artificial neural network (ANN). The paper details a unique, window based learning algorithm using the Effective Boltzmann Machine (EBM). In the past, EBM, which is based on the Boltzmann Machine (BM), has been shown to have the ability to perform pattern completion and to provide an energy measure for completions of any length. Described in the paper is the way that the EBM itself is a highly suitable architecture for learning window based problems. A walk through of a simple example, mathematical derivation as well as simulation experiments shows that the EBM outperforms a window based BM using the criteria of quality of learning, and speed of learning, as well as the resultant generalisations produced by the network.