Rules of thumb for input size in Deep Neural Network

I was wondering if there is any rules of thumb for the input size of a Deep Neural Network in a regression case with time series data?

I mean, should the number of features be equal to a certain multiple of the number of examples used in input ? (when I an choosing the window size aka the number of features in input) Cheers !