In applied mathematics, the starred transform, or star transform, is a discrete-time variation of the Laplace transform, so-named because of the asterisk or "star" in the customary notation of the sampled signals. The transform is an operator of a continuous-time function x ( t ) {\displaystyle x(t)} , which is transformed to a function X ∗ ( s ) {\displaystyle X^{*}(s)} in the following manner:
X ∗ ( s ) = L [ x ( t ) ⋅ δ T ( t ) ] = L [ x ∗ ( t ) ] , {\displaystyle {\begin{aligned}X^{*}(s)={\mathcal {L}}[x(t)\cdot \delta _{T}(t)]={\mathcal {L}}[x^{*}(t)],\end{aligned}}}
where δ T ( t ) {\displaystyle \delta _{T}(t)} is a Dirac comb function, with period of time T. The starred transform is a convenient mathematical abstraction that represents the Laplace transform of an impulse sampled function x ∗ ( t ) {\displaystyle x^{*}(t)} , which is the output of an ideal sampler, whose input is a continuous function, x ( t ) {\displaystyle x(t)} . The starred transform is similar to the Z transform, with a simple change of variables, where the starred transform is explicitly declared in terms of the sampling period (T), while the Z transform is performed on a discrete signal and is independent of the sampling period. This makes the starred transform a de-normalized version of the one-sided Z-transform, as it restores the dependence on sampling parameter T.
Relation to Laplace transform Since X ∗ ( s ) = L [ x ∗ ( t ) ] {\displaystyle X^{*}(s)={\mathcal {L}}[x^{*}(t)]} , where:
x ∗ ( t ) = d e f x ( t ) ⋅ δ T ( t ) = x ( t ) ⋅ ∑ n = 0 ∞ δ ( t − n T ) . {\displaystyle {\begin{aligned}x^{*}(t)\ {\stackrel {\mathrm {def} }{=}}\ x(t)\cdot \delta _{T}(t)&=x(t)\cdot \sum _{n=0}^{\infty }\delta (t-nT).\end{aligned}}}
Then per the convolution theorem, the starred transform is equivalent to the complex convolution of L [ x ( t ) ] = X ( s ) {\displaystyle {\mathcal {L}}[x(t)]=X(s)} and L [ δ T ( t ) ] = 1 1 − e − T s {\displaystyle {\mathcal {L}}[\delta _{T}(t)]={\frac {1}{1-e^{-Ts}}}} , hence:
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