Transfer function H(z) in Signal Processing - Time & Space Complexity
We want to understand how the time to compute the transfer function H(z) changes as the input size grows.
How does the number of calculations grow when we increase the length of the input signal or filter coefficients?
Analyze the time complexity of the following code snippet.
# Compute output y[n] using transfer function H(z)
for n in range(len(x)):
y[n] = 0
for k in range(len(h)):
if n - k >= 0:
y[n] += h[k] * x[n - k]
This code calculates the output signal y by applying the filter coefficients h to the input signal x using convolution.
Identify the loops, recursion, array traversals that repeat.
- Primary operation: Nested loops performing multiplications and additions for convolution.
- How many times: Outer loop runs for each input sample (n times), inner loop runs for each filter coefficient (m times).
As the input size or filter length grows, the total operations increase by multiplying these sizes.
| Input Size (n) | Filter Length (m) | Approx. Operations |
|---|---|---|
| 10 | 5 | 50 |
| 100 | 5 | 500 |
| 1000 | 5 | 5000 |
Pattern observation: Operations grow proportionally to the product of input size and filter length.
Time Complexity: O(n * m)
This means the time to compute grows in direct proportion to both the input length and the filter size.
[X] Wrong: "The time to compute H(z) depends only on the input size n."
[OK] Correct: The filter length m also affects the total work because each input sample is combined with all filter coefficients.
Understanding how nested loops affect time helps you explain performance in signal processing tasks clearly and confidently.
"What if the filter length m is fixed and very small? How would the time complexity change as input size n grows?"
Practice
H(z) represent in signal processing?Solution
Step 1: Understand the definition of transfer function
The transfer functionH(z)is defined as the ratio of the output signal to the input signal in the z-domain.Step 2: Identify the correct description
Among the options, only The ratio of output to input signals in the z-domain correctly describesH(z)as this ratio.Final Answer:
The ratio of output to input signals in the z-domain -> Option DQuick Check:
Transfer function = output/input ratio [OK]
- Confusing H(z) with time delay
- Thinking H(z) is just frequency
- Mixing amplitude with transfer function
H(z)?Solution
Step 1: Recall the standard form of digital filter transfer function
The transfer function is usually expressed with negative powers of z, representing delays: numerator and denominator polynomials in z^{-1}.Step 2: Compare options with the standard form
H(z) = (b0 + b1z^{-1} + b2z^{-2}) / (1 + a1z^{-1} + a2z^{-2}) correctly shows numerator and denominator with negative powers of z, matching the standard form.Final Answer:
H(z) = (b0 + b1z^{-1} + b2z^{-2}) / (1 + a1z^{-1} + a2z^{-2}) -> Option CQuick Check:
Negative powers of z indicate delays [OK]
- Using positive powers of z incorrectly
- Multiplying numerator and denominator instead of dividing
- Forgetting the leading 1 in denominator
H(z) = (1 - 0.5z^{-1}) / (1 - 0.9z^{-1} + 0.15z^{-2}), what is the value of H(z) at z = 1?Solution
Step 1: Substitute z = 1 into H(z)
Calculate numerator: 1 - 0.5 * 1^{-1} = 1 - 0.5 = 0.5
Calculate denominator: 1 - 0.9 * 1^{-1} + 0.15 * 1^{-2} = 1 - 0.9 + 0.15 = 0.25Step 2: Compute H(1) = numerator / denominator
H(1) = 0.5 / 0.25 = 2.0 exactly.Final Answer:
2.0 -> Option AQuick Check:
H(1) = 2.0 [OK]
- Forgetting to use z^{-1} as 1/z
- Incorrect arithmetic in numerator or denominator
- Choosing zero instead of computed value
H(z) = (1 + 0.3z^{-1} - 0.2z^{-2}) / (1 + 0.5z + 0.1z^{-2})Solution
Step 1: Examine powers of z in numerator and denominator
The numerator has negative powers of z, which is correct for delays.
The denominator has a positive power term0.5z, which is not standard and incorrect.Step 2: Confirm correct form of denominator
The denominator should have terms with negative powers of z (delays), not positive powers (advances). So the positive power term is an error.Final Answer:
Denominator has a positive power of z which is incorrect -> Option BQuick Check:
Denominator powers must be negative [OK]
- Allowing positive powers of z in denominator
- Confusing numerator and denominator powers
- Thinking number of terms limits validity
H(z) = (1 - 0.7z^{-1}) / (1 - 1.2z^{-1} + 0.45z^{-2}). Which statement best describes the system's stability based on the poles of H(z)?Solution
Step 1: Find the poles by solving denominator polynomial
The denominator is 1 - 1.2z^{-1} + 0.45z^{-2} = 0.
Rewrite as z^2 - 1.2z + 0.45 = 0 (multiply both sides by z^2).Step 2: Calculate roots of the quadratic
Using quadratic formula:
z = [1.2 ± sqrt(1.44 - 1.8)] / 2
Discriminant = 1.44 - 1.8 = -0.36 (complex roots)
Roots: z = 0.6 ± 0.3iStep 3: Calculate magnitude of poles
Magnitude = sqrt(0.6^2 + 0.3^2) = sqrt(0.36 + 0.09) = sqrt(0.45) ≈ 0.67 < 1Step 4: Re-examine coefficients for stability
Actually, the denominator polynomial is in z^{-1}, so poles are roots of denominator polynomial in z.
But the coefficients suggest poles inside unit circle, so system is stable.Step 5: Check option correctness
Options say system is unstable if poles outside unit circle.
Our calculation shows poles inside unit circle, so system is stable.Final Answer:
The system is stable because all poles lie inside the unit circle -> Option AQuick Check:
Poles magnitude < 1 means stable [OK]
- Confusing zeros with poles for stability
- Ignoring complex roots magnitude
- Assuming zeros affect stability
Ready to prove it?
Pass the test and this pattern moves unknown
