Batch backpropagation has a similar formula as vanilla backpropagation. The difference lies in the time when the update of the links takes place. While in vanilla backpropagation an update step is performed after each single pattern, in batch backpropagation all weight changes are summed over a full presentation of all training patterns (one epoch). Only then, an update with the accumulated weight changes is performed. This update behavior is especially well suited for training pattern parallel implementations where communication costs are critical.