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{{Cleanup rewrite|it is written like a tutorial|FIR transfer function|date=December 2020}}[[Filter (signal processing)#The transfer function|Transfer function filter]] utilizes the transfer function and the [[Convolution theorem]] to produce a filter. In this article, an example of such a filter using finite impulse response is discussed and an application of the filter into real world data is shown.
== FIR (Finite Impulse Response) Linear filters ==
In digital signal processing, an [[Finite impulse response|FIR filter]] is a time-continuous filter that is invariant with time. This means that the filter does not depend on the specific point of time, but rather depends on the time duration. The specification of this filter uses a [[Linear filter#FIR transfer functions|transfer function]]
== Mathematical model ==
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:<math>h(t) = \begin{cases} 0, & \forall &-\infty &\le & t &\le 0 \\ e^{-t}, \quad & \forall &0 &\le & t &\le +\infty \end{cases}</math>
[[File:Single sided filter frequency response.jpg|Single sided filter frequency response]]
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