A linear response function describes the inputoutput relationship of a signal transducer such as a radio turning electromagnetic waves into music or a neuron turning synaptic input into a response. Because of its many applications in information theory, physics and engineering there exist alternative names for specific linear response functions such as susceptibility or impedance. The concept of a Green's function or fundamental solution of an ordinary differential equation is closely related.
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Denote the input of a system by h(t), and the response of the system by o(t). Generally, the value of o(t) will depend not only on the present value of h(t), but also on past values. Approximately o(t) is a weighted sum of the previous values of h(t'), with the weights given by the linear response function χ(t − t'):
This expression is the leading order term of a Volterraexpansion. If the system in question is highly nonlinear, higher order terms become important and the signal transducer can not adequately be described just by its linear response function.
The Fourier transform of the linear response function is very useful as it describes the output of the system if the input is a sine wave i(t) = i_{0}sin(ωt) with frequency ω. The output reads
with amplitude gain and phase shift .
Consider the damped harmonic oscillator, which gets an external driving by the input i(t)
The Fourier transform of the linear response function is given as
From this representation, we see that the Fourier transform of the linear response function attains a maximum for : The damped harmonic oscillator acts as a band pass filter.
