Inheriting knowledge in neural networks

The problem of inheriting knowledge between different networks is examined. Such inheritance allows speeding up training, avoiding some local minima, and coupling fast training networks to fast executing networks. After formulating the general approach, the technique is illustrated and equations are derived for the case of transferring knowledge between a two-layer net and a three-layer net. The equations are written and solved using symbolic algebra techniques for the ease of the XOR