Least Mean Squares (LMS) Filter Weight Update I have a general question regarding Least mean squares adaptive filters.

Using the example of noise cancellation, I understand that if you have a set of reference signals (S) and corrupted signals (S+N) then you can perform minimisation of the error to find the optimal weights for the set of inputs.

I am wondering if this is normally performed 'offline' or if this can be performed on the fly with the weights changing over time?
That really depends on context, but generally adaptive implies that the calculations are done on-line / on the fly.

In some applications, the filter is updated for a while, then the adaptation is turned off and the last lot of weights are used.