I’m developing the spatial pooling algorithm for learning image recognition. For example, the learning process needs 3 to 4 iterations to stable state (which means that chosen columns are same over iterations). However, after around 50 iterations, the boosting factor affects to the process and the result of active columns is unstable. My question is: why do we need boosting when we know it would affect badly to the stability of our result. With the boosting factors, we will never reach the stable state of the learning if I understand it correctly.