title: Neural network back propagation weight change effect on predictions
body: <p>I am trying to understand how neural network can predict different outputs by learning different input/output patterns..I know that weights changes are the mode of learning...but if an input brings about weight adjustments to achieve a particular output  in back propagtion algorithm.. won't this knowledge(weight updates) be knocked of when presented with a different set of input pattern...thus making the network forget what it had previously learnt..</p>