Analyzing Cross-Connected Networks

The nonlinear complexities of neural networks make network solutions difficult to understand. Sanger's contributionanalysis is here extended to the analysis of networks automatically generated by the cascadecorrelation learning algorithm. Because such networks have cross of hiddenconnections that supersede hidden layers, standard analyses contribution is defined as theunit activation patterns are insufficient. A of an output weight and the associated activation on the sendingproduct unit, whether that sending unit is an input or a hidden unit, multiplied by the sign of the output target for the current input pattern.