Feedforward Neural Network Methodology

This monograph provides a thorough and coherent introduction to the ma thematical properties of feedforward neural networks and to the comput ationally intensive methodology that has enabled their highly successf ul application to complex problems of pattern classification, forecast ing, regression, and nonlinear systems modeling. The reader is provide d with the information needed to make practical use of the powerful mo deling and design tool of feedforward neural networks, as well as pres ented with the background needed to make contributions to several rese arch frontiers. This work is therefore of interest to those in electri cal engineering, operations research, computer science, and statistics who would like to use nonlinear modeling of stochastic phenomena to t reat problems of pattern classification, forecasting, signal processin g, machine intelligence, and nonlinear regression.