# Offline training or batch wise training

Can somebody please explain how to train a neural network in batch mode. I have a single target time series of length $N$ for a given input time series of the same length. In order to apply Hopfield network's content addressable property, I want to store this pattern of input time series. Then given a test time series that is a noisy version, how do I apply Hopfield neural network with Particle Swarm or Genetic algorithm as a learning method with the MSE as the fitness function? All this is confusing, since I am well practiced with incremental training and not batch wise training. PSO or GA update their equations for every input, so how do I adapt this with batch wise training. Insights on this technique will help to clear away the confusions. Thank you