Many techniques for time-series or sequential data work by taking a fixed size window, that is the last N items of the series, and then use each wondow as if it were separate data, eiethre for training ro execution. Examples include moving average methods in time series analysis, simple Markov models and applying neural networks to the data windows. Wondowing methods are always finite impluse response as data outside of the wondow cannot affect the current response.
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