Proof of Z-Transform Property | X(z) and x(n) Relation

In summary, to show that Z\{x^{*}(n)\}=X^{*}(z^{*}), we use the definition of the z-transform and the properties of complex conjugates. By substituting x(n) = x_{R}(n) + jx_{I}(n) and x^{*}(n) = x_{R}(n) - jx_{I}(n) into the z-transform definition, we can show that Z\{x^{*}(n)\}=X^{*}(z^{*}). However, further simplification is needed to complete the proof.
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Homework Statement



Using the definition of the z-transform, show that if [tex]X(z)[/tex] is the z-transform of [tex]x(n) = x_{R}(n) +jx_{I}(n)[/tex], then:
[tex]Z\{x^{*}(n)\}=X^{*}(z^{*})[/tex]

Homework Equations



z-tranform definition:

[tex]Z\{x(n)\}=X(z)=\sum x(n)z^{-n}[/tex]

The Attempt at a Solution



[tex]x(n) = x_{R}(n) + jx_{I}(n) \Longrightarrow x^{*}(n) = x_{R}(n) - jx_{I}(n)[/tex]

[tex]Z\{x^{*}(n)\}=Z\{x_{R}(n) - jx_{I}(n)\}=\sum x^{*}(n)z^{-n}[/tex]

[tex]=\sum [x_{R}(n) - jx_{I}(n)]z^{-n}[/tex]

[tex]=\sum [x_{R}(n)z^{-n} - jx_{I}(n)z^{-n}][/tex][tex]=\sum x_{R}(n)z^{-n} - j \sum x_{I}(n)z^{-n}[/tex]
 
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This is where I am stuck. Am I going in the right direction?
 

FAQ: Proof of Z-Transform Property | X(z) and x(n) Relation

What is the Z-transform and how is it related to x(n)?

The Z-transform is a mathematical tool used to convert a discrete-time signal x(n) into a complex-valued function X(z). This function represents the frequency domain representation of x(n) and can be used to analyze and manipulate the signal in the frequency domain.

What is the Z-transform property of linearity and how does it relate to x(n)?

The Z-transform property of linearity states that if a signal x(n) is a linear combination of two other signals, say x1(n) and x2(n), then the Z-transform of x(n) will be the same linear combination of the Z-transforms of x1(n) and x2(n). This property is useful in simplifying calculations and analyzing complex signals in the frequency domain.

What is the significance of the Z-transform property of time shifting in relation to x(n)?

The Z-transform property of time shifting states that if a signal x(n) is delayed or advanced by a certain number of samples, then its Z-transform will be multiplied by a corresponding exponential term. This property is useful in analyzing signals with time delays and in designing filters with specific phase characteristics.

How does the Z-transform property of scaling relate to x(n)?

The Z-transform property of scaling states that if a signal x(n) is multiplied by a constant, then its Z-transform will be the same signal multiplied by the same constant. This property is useful in analyzing signals with different amplitudes and in designing filters with specific gain characteristics.

What is the inverse Z-transform and how is it related to X(z)?

The inverse Z-transform is the process of converting a complex-valued function X(z) back into a discrete-time signal x(n). This is useful in implementing filters and other signal processing operations in the time domain.

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