Z-transform definition in Signal Processing - Time & Space Complexity

Time Complexity: Z-transform definition

O(n)

Understanding Time Complexity

We want to understand how the time to compute the Z-transform changes as the input signal length grows.

How does the number of calculations grow when the signal gets longer?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

// Compute Z-transform for a discrete signal x[n]
function z_transform(x, z) {
  let X = 0;
  for (let n = 0; n < x.length; n++) {
    X += x[n] * Math.pow(z, -n);
  }
  return X;
}
    

This code calculates the Z-transform by summing the signal values multiplied by powers of z.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Loop over each element of the input signal array.
• How many times: Exactly once for each element, so as many times as the signal length.

How Execution Grows With Input

As the signal length grows, the number of calculations grows in the same way.

Input Size (n)	Approx. Operations
10	10
100	100
1000	1000

Pattern observation: Doubling the input size doubles the work needed.

Final Time Complexity

Time Complexity: O(n)

This means the time to compute the Z-transform grows linearly with the signal length.

Common Mistake

[X] Wrong: "The Z-transform calculation takes the same time no matter how long the signal is."

[OK] Correct: Each signal value must be processed once, so longer signals need more steps.

Interview Connect

Understanding how the Z-transform computation scales helps you explain efficiency in signal processing tasks clearly and confidently.

Self-Check

"What if we only compute the Z-transform for every other sample? How would the time complexity change?"

Practice

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

easy

A. To convert discrete-time signals into a complex frequency domain for easier analysis

B. To convert continuous signals into discrete signals

C. To amplify the signal strength

D. To filter out noise from signals

Solution

1. Step 1: Understand the role of Z-transform

   The Z-transform changes discrete-time signals into a complex frequency domain representation.

2. Step 2: Compare options with definition

   Only To convert discrete-time signals into a complex frequency domain for easier analysis correctly describes this transformation purpose.

3. Final Answer:

   To convert discrete-time signals into a complex frequency domain for easier analysis -> Option A

4. Quick Check:

   Z-transform = frequency domain conversion [OK]

Hint: Z-transform moves signals to complex frequency domain [OK]

Common Mistakes:

• Confusing Z-transform with filtering
• Thinking it converts continuous to discrete signals
• Assuming it amplifies signals

2. Which of the following is the correct formula for the Z-transform of a discrete sequence x[n]?

easy

A. X(z) = \sum_{n=-\infty}^{\infty} x[n] z^n

B. X(z) = \sum_{n=0}^{\infty} x[n] z^{-n}

C. X(z) = \int_{-\infty}^{\infty} x(t) e^{-j\omega t} dt

D. X(z) = \sum_{n=0}^{N} x[n] z^n

Solution

1. Step 1: Recall the Z-transform formula

   The Z-transform is defined as X(z) = sum from n=0 to infinity of x[n] times z to the power -n.

2. Step 2: Match formula with options

   X(z) = \sum_{n=0}^{\infty} x[n] z^{-n} matches the standard Z-transform formula exactly.

3. Final Answer:

   X(z) = \sum_{n=0}^{\infty} x[n] z^{-n} -> Option B

4. Quick Check:

   Z-transform formula = sum x[n] z^-n [OK]

Hint: Look for sum from 0 to infinity with z to negative n [OK]

Common Mistakes:

• Using positive powers of z instead of negative
• Confusing Z-transform with Fourier transform integral
• Summing over all integers instead of starting at 0

3. Given the sequence x[n] = {1, 2, 3} for n=0,1,2 and zero elsewhere, what is the Z-transform X(z)?

medium

A. X(z) = 1z^{-1} + 2z^{-2} + 3z^{-3}

B. X(z) = 1 + 2z + 3z^{2}

C. X(z) = 1 + 2z^{-1} + 3z^{-2}

D. X(z) = 1z + 2z^{2} + 3z^{3}

Solution

1. Step 1: Apply Z-transform formula to given sequence

   Use X(z) = sum x[n] z^{-n} from n=0 to 2: 1*z^0 + 2*z^{-1} + 3*z^{-2}.

2. Step 2: Write the expression clearly

   This equals 1 + 2z^{-1} + 3z^{-2}, matching X(z) = 1 + 2z^{-1} + 3z^{-2}.

3. Final Answer:

   1 + 2z^{-1} + 3z^{-2} -> Option C

4. Quick Check:

   Sum x[n] z^-n = 1+2z^-1+3z^-2 [OK]

Hint: Use powers of z as negative indices matching n [OK]

Common Mistakes:

• Using positive powers of z
• Starting sum at n=1 instead of 0
• Ignoring zero values outside given n

4. Identify the error in this Z-transform expression: X(z) = \sum_{n=0}^{\infty} x[n] z^{n}

medium

A. The variable z should be real, not complex

B. The summation limits are incorrect

C. The sequence x[n] should be continuous, not discrete

D. The power of z should be negative, not positive

Solution

1. Step 1: Review the Z-transform formula

   The Z-transform uses z raised to the negative power of n, i.e., z^{-n}.

2. Step 2: Compare with given expression

   The expression uses z^{n} (positive power), which is incorrect.

3. Final Answer:

   The power of z should be negative, not positive -> Option D

4. Quick Check:

   Z-transform uses z^-n, not z^n [OK]

Hint: Check sign of exponent on z carefully [OK]

Common Mistakes:

• Using positive powers of z
• Misunderstanding summation limits
• Confusing discrete and continuous signals

5. You have a signal x[n] defined as 1 for n=0 to 3 and 0 elsewhere. How would you express its Z-transform X(z) and what does it represent?

hard

A. X(z) = 1 + z^{-1} + z^{-2} + z^{-3}, representing the signal's frequency components

B. X(z) = z + z^{2} + z^{3} + z^{4}, representing the time-domain signal

C. X(z) = \sum_{n=0}^{\infty} x[n] z^{n}, representing the signal's energy

D. X(z) = 1 + 2z^{-1} + 3z^{-2} + 4z^{-3}, representing the signal's amplitude

Solution

1. Step 1: Write the Z-transform for given x[n]

   Since x[n] = 1 for n=0 to 3, X(z) = sum from 0 to 3 of 1*z^{-n} = 1 + z^{-1} + z^{-2} + z^{-3}.

2. Step 2: Understand what X(z) represents

   X(z) shows the signal's frequency components in the complex z-plane.

3. Final Answer:

   X(z) = 1 + z^{-1} + z^{-2} + z^{-3}, representing the signal's frequency components -> Option A

4. Quick Check:

   Sum of z^-n terms = frequency components [OK]

Hint: Sum z^-n terms for signal duration [OK]

Common Mistakes:

• Using positive powers of z
• Incorrect coefficients in sum
• Misinterpreting what X(z) represents