Complexity measures for classes of neural networks with variable weight bounds
William Finnoff · 1991
The author derives complexity measures for classes of single-hidden-layer feedforward networks based on the capacity and metric entropy of a class of functions. Based on these measures, some deficiencies in commonly used complexity-penalty terms implemented to prevent overfitting are indicated.>