The effect of random errors on a large statistical energy analysis model

The framework of analysis known as Statistical Energy Analysis has many important applications particularly in systems where detailed information is not available. As a result of the approximations made, to simplify the calculations, random error can be introduced into the SEA model. For large systems this gives rise to uncertainty in the energy levels. It is shown that the effect of these errors on the model depends on the “shape” of the model. A compact model dominated by short paths is less affected than a model controlled by long paths. In either case the ratio of the average error in the resultant energy level to the average error in the coupling loss factor decreases as the errors increase. This means that large models may be used with confidence even when based on data that is known to be approximate.