Linear time-invariant (LTI) systems are
systems that are both linear and time-invariant.
Linearity states that when a linear combination of the two inputs is fed to the system, the output of
the system is a linear
combination of the respective outputs.
Let x1(t) and x2(t) be
any two signals. Suppose that the output of a system to x1(t) is y1(t)
and the output of the system to x2(t) is y2(t). If this
always implies that the output of the system to α1 x1(t)+α2
x2(t) is α1 y1(t) + α2 y2(t),
then the system is linear and the superposition principle is said to hold.
A system is said to be time invariant if when
y(t) is the output that corresponds to x(t), then for any τ, y (t − τ) is the
output that corresponds to x (t − τ).
LTI systems are so important –
1. Because many systems encountered in
nature can be successfully modeled as LTI systems.
2. For linear time invariant system, we only need to
know the impulse response h(t) of the system (or equivalently frequency
response H(ω))
in order to predict the output of the system in response to any input. This is
done by convoluting the input with the impulse response. So a linear time invariant system is a lot easier to analyze.
So LTI systems can be analyzed in
considerable detail, providing insight into their properties
This is not true for nonlinear or time
variant system.
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