I'm having trouble with some of the concepts in machine learning through neural networks. One of them is backpropagation. In the weight updating equation,

delta_w = a*(t - y)*g'(h)*x

t is the "target output", which would be your class label, or something, in the case of supervised learning. But what would the "target output" be for unsupervised learning?

Can someone kindly provide an example of how you'd use BP in unsupervised learning, specifically for clustering of classification?

Thanks in advance.