Signals: Fourier series and frequency response

In summary, the conversation discusses a recursive DT system with input x[n] and output y[n], and explores its impulse response, classification, modification for unit DC gain, and comparison to another recursive system. The provided equations and attempts at finding a solution are also mentioned. The main difficulties lie in understanding the conversion between an impulse response and frequency response, as well as the role of complex numbers in the analysis. Part d) is unclear in terms of what is being compared.
  • #1
Zablorg
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Homework Statement



A recursive DT system with input x[n] and output y[n] is given by

y[n] = -0.25y[n-2] + x[n]

a) Determine and plot the impulse response h[n] such that y[n] = x[n]*h[n]

b) how would you classify the system and why?

c) What modification, if any, should be made so that the system has unit DC gain?

d) Another recursive DT LTI system has an impulse response given by

g[n] = δ[n-1] - (1/4)δ[n-2] + (1/16)δ[n-3] - (1/64)δ[n-4] + (1/128)δ[n-5]...

By comparing with part (a), or otherwise, what is a recursive system which has g[n] as an impulse response?

Homework Equations



1) Assume that if x[n] is 0 while n < 0, y[n] is also 0 while n < 0

2) H(z) = [itex]\sum[/itex]h[k]z-k from k = -∞ to ∞

The Attempt at a Solution



I've got part a) down: substituting x[n] = δ[n] and starting from n = 0, we see that h[0] = 1, h[2] = -1/4, h[4] = 1/16, etc, with h[n] = 0 for odd values of n. We can represent this mathematically as:

h[n] = (-0.25)0.5n

Parts b) and c) are the ones that are confusing me right now, because despite consulting the textbook many times I am conceptually having enormous difficulty understanding the conversion between an impulse response and the corresponding frequency response, particularly for a DT system like what's being shown here. For b) and c), I expect I'd need an equation that would express the frequency response directly in terms of frequency, rather than evaluate a given number of frequencies and analyse them.

I think the difficulty comes from the complex number z. Even if I was to evaluate the expressions manually, what would I change z to each time? The same question holds true for evaluating it for any given z. I think fundamentally I'm not appreciating the role that the complex number plays in the analysis.
 
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  • #2
I'd really appreciate some help. For part d), I don't understand what the question is asking. What does it mean to compare it with part a)?
 

FAQ: Signals: Fourier series and frequency response

1. What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sine and cosine waves of different frequencies. It is used to analyze and manipulate signals in various fields such as engineering, physics, and mathematics.

2. How is a Fourier series related to frequency analysis?

A Fourier series decomposes a signal into its individual frequency components, allowing for a more detailed analysis of the signal's frequency content. This is useful in understanding the behavior and characteristics of the signal.

3. What is the significance of the frequency response in signal processing?

The frequency response is a measure of how a system or signal processor responds to different frequencies. It is commonly used in designing filters and other signal processing techniques to alter the frequency content of a signal.

4. Can a non-periodic signal be represented by a Fourier series?

No, a Fourier series is only applicable to periodic signals. However, non-periodic signals can be represented by a Fourier transform, which is a generalization of the Fourier series for non-periodic signals.

5. What are some practical applications of Fourier series and frequency response?

Fourier series and frequency response have various applications in fields such as telecommunications, audio and video processing, medical imaging, and control systems. They are also essential in analyzing and understanding signals in physics and engineering experiments.

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