Introduction - If you have any usage issues, please Google them yourself
If output is "0", that is the result error, then adjust the weight of network connection to reduce the direction of the comprehensive input weighted value. The purpose is to reduce the possibility of making the same mistake when the network enters the "A" mode again. In this way, when we input several handwritten letters "A" and "B" into the network, the accuracy of network judgement will be greatly improved after several times of learning by network. This shows that the network has been successful in learning the two patterns, and it has distributed the two patterns in the network's various connection weights. When the network meets any of them again, it can make quick and accurate judgment and recognition. In general, the more the number of neurons in the network is, the more patterns it can remember and recognize.