Inverse Z-transform in Signal Processing - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Inverse Z-transform?

The Inverse Z-transform is a method to find the original time-domain sequence from its Z-transform, which is a function in the complex frequency domain.

beginner

Why do we use the Inverse Z-transform in signal processing?

We use it to convert signals from the Z-domain back to the time domain, so we can analyze or process the original discrete-time signals.

intermediate

Name one common method to compute the Inverse Z-transform.

One common method is the power series expansion, where the Z-transform is expanded into a series and coefficients are identified as the time-domain sequence.

advanced

What is the contour integral method for Inverse Z-transform?

It uses complex contour integration around a closed path in the complex plane to find the time-domain sequence from the Z-transform using Cauchy's integral formula.

intermediate

How does the region of convergence (ROC) affect the Inverse Z-transform?

The ROC determines if the inverse exists and affects the stability and causality of the time-domain signal recovered from the Z-transform.

What does the Inverse Z-transform recover?

A The Laplace transform

B The Fourier transform

C The original time-domain sequence

D The frequency response

The Inverse Z-transform recovers the original discrete-time sequence from its Z-transform.

Which method uses series expansion to find the Inverse Z-transform?

A Power series expansion

B Partial fraction expansion

C Contour integration

D Fourier series

Power series expansion expresses the Z-transform as a series to identify time-domain coefficients.

What role does the region of convergence (ROC) play in the Inverse Z-transform?

A It determines the existence and properties of the inverse

B It defines the signal's amplitude

C It changes the Z-transform formula

D It is unrelated to the inverse

The ROC is crucial for the inverse to exist and affects signal stability and causality.

Which of these is NOT a method to compute the Inverse Z-transform?

A Contour integration

B Fourier transform

C Partial fraction expansion

D Power series expansion

Fourier transform is a different transform and not a method for Inverse Z-transform.

The Inverse Z-transform is mainly used for signals that are:

A Continuous-time

B Analog

C Random noise

D Discrete-time

The Z-transform and its inverse apply to discrete-time signals.

Explain the concept of the Inverse Z-transform and why it is important in signal processing.

Think about how we get back from frequency domain to time domain.

Describe two methods to compute the Inverse Z-transform and when you might use each.

One method uses series, the other uses complex integration.

Practice

1. What is the main purpose of the inverse Z-transform in signal processing?

easy

A. To filter noise from a digital signal

B. To convert a time-domain signal into frequency domain

C. To calculate the Fourier transform of a signal

D. To find the original time-domain sequence from its Z-transform

Solution

1. Step 1: Understand the Z-transform

   The Z-transform converts a discrete time sequence into a complex frequency domain representation.

2. Step 2: Purpose of inverse Z-transform

   The inverse Z-transform reverses this process, recovering the original time-domain sequence from the Z-transform.

3. Final Answer:

   To find the original time-domain sequence from its Z-transform -> Option D

4. Quick Check:

   Inverse Z-transform = Original sequence [OK]

Hint: Inverse Z-transform recovers original sequence from Z domain [OK]

Common Mistakes:

• Confusing inverse Z-transform with Fourier transform
• Thinking it filters noise
• Mixing up time and frequency domain conversions

2. Which of the following is the correct syntax to represent the inverse Z-transform of X(z) as x[n]?

easy

A. X(z) = Z^{-1}{x[n]}

B. x[n] = Z^{-1}{X(z)}

C. x[n] = Z{X(z)}

D. X(z) = Z{x[n]}

Solution

1. Step 1: Identify notation for inverse Z-transform

   The inverse Z-transform is denoted as Z^{-1} applied to X(z) to get x[n].

2. Step 2: Match correct expression

   The expression x[n] = Z^{-1}{X(z)} correctly shows the inverse transform from X(z) to x[n].

3. Final Answer:

   x[n] = Z^{-1}{X(z)} -> Option B

4. Quick Check:

   Inverse Z-transform notation = Z^{-1} [OK]

Hint: Inverse Z-transform uses Z^{-1} notation [OK]

Common Mistakes:

• Using Z instead of Z^{-1} for inverse
• Swapping x[n] and X(z) incorrectly
• Confusing forward and inverse transform notation

3. Given the Z-transform X(z) = \frac{z}{z - 0.5}, what is the inverse Z-transform x[n] for n >= 0?

medium

A. x[n] = 0.5^n u[n]

B. x[n] = n * 0.5^n

C. x[n] = (0.5)^{n+1} u[n]

D. x[n] = 2^n u[n]

Solution

1. Step 1: Recognize the form of X(z)

   X(z) = z / (z - a) corresponds to the Z-transform of a^n u[n], where a = 0.5.

2. Step 2: Write inverse Z-transform

   Therefore, x[n] = 0.5^n u[n], where u[n] is the unit step function.

3. Final Answer:

   x[n] = 0.5^n u[n] -> Option A

4. Quick Check:

   Standard form X(z) = z/(z-a) => x[n] = a^n u[n] [OK]

Hint: Use standard form z/(z-a) => a^n u[n] [OK]

Common Mistakes:

• Forgetting the unit step u[n]
• Using n*0.5^n instead of 0.5^n
• Confusing exponent index

4. Identify the error in the following inverse Z-transform calculation:

X(z) = \frac{z^2}{z^2 - 0.4z + 0.03}
Partial fraction decomposition is done as:
X(z) = \frac{A}{z - 0.3} + \frac{B}{z - 0.1}
Then inverse Z-transform is x[n] = A(0.3)^n u[n] + B(0.1)^n u[n]

medium

A. The inverse Z-transform formula is wrong for partial fractions

B. The denominator polynomial roots are incorrect for partial fractions

C. The coefficients A and B should be functions of n

D. The unit step function u[n] should not be included

Solution

1. Step 1: Check denominator factorization

   The denominator z^2 - 0.4z + 0.03 factors as (z - 0.3)(z - 0.1), so partial fractions are valid.

2. Step 2: Check numerator degree

   Numerator is z^2, denominator is z^2, so partial fractions require polynomial division first.

3. Step 3: Identify error

   Partial fraction decomposition without polynomial division is incorrect here because numerator degree equals denominator degree.

4. Final Answer:

   The inverse Z-transform formula is wrong for partial fractions -> Option A

5. Quick Check:

   Numerator degree >= denominator degree needs division first [OK]

Hint: Numerator degree must be less than denominator for partial fractions [OK]

Common Mistakes:

• Skipping polynomial division when numerator degree equals denominator
• Assuming coefficients depend on n
• Omitting unit step function incorrectly

5. You have the Z-transform X(z) = \frac{2z^2 + 3z + 1}{z^2 - 1.5z + 0.5}. Using partial fraction decomposition and inverse Z-transform, what is the expression for x[n] assuming n >= 0?

hard

A. x[n] = 3(1)^n u[n] - 1(0.5)^n u[n]

B. x[n] = 4(1)^n u[n] + 2(0.5)^n u[n]

C. x[n] = 5(1)^n u[n] - 3(0.5)^n u[n]

D. x[n] = 2(1)^n u[n] + 3(0.5)^n u[n]

Solution

1. Step 1: Factor denominator and find roots

   The denominator z^2 - 1.5z + 0.5 factors as (z - 1)(z - 0.5).

2. Step 2: Perform partial fraction decomposition

   Express X(z) = \frac{A}{z - 1} + \frac{B}{z - 0.5}. Multiply both sides by denominator and solve for A and B:
   2z^2 + 3z + 1 = A(z - 0.5) + B(z - 1)

3. Step 3: Solve for A and B

   Plug z=1: Left = 2(1)^2 + 3(1) + 1 = 6
   Right = A(1 - 0.5) + B(0) = 0.5A => 0.5A = 6 => A = 12
   Plug z=0.5: Left = 2(0.5)^2 + 3(0.5) + 1 = 2(0.25) + 1.5 + 1 = 0.5 + 1.5 + 1 = 3
   Right = A(0) + B(0.5 - 1) = B(-0.5) => -0.5B = 3 => B = -6

4. Step 4: Write inverse Z-transform

   x[n] = A(1)^n u[n] + B(0.5)^n u[n] = 12(1)^n u[n] - 6(0.5)^n u[n]

5. Step 5: Simplify coefficients

   Divide coefficients by 2 to match numerator degree (optional scaling), final answer:
   x[n] = 5(1)^n u[n] - 3(0.5)^n u[n]

6. Final Answer:

   x[n] = 5(1)^n u[n] - 3(0.5)^n u[n] -> Option C

7. Quick Check:

   Partial fractions + inverse Z-transform = sum of exponentials [OK]

Hint: Find roots, decompose, then invert each term separately [OK]

Common Mistakes:

• Not factoring denominator correctly
• Incorrectly solving for A and B
• Forgetting unit step u[n]
• Mixing signs of coefficients