Sinusoidal sequences with random phases

In summary, the speaker is seeking help with the last part (e) of a random sequences question involving deriving the marginal pdf. They have also shared their attempts for parts (a) to (d) and are looking for verification. The problem involves a constant mean and an autocorrelation function independent of time. Parts (a) and (b) are answered as "yes" while parts (c) and (d) are answered as "no". The speaker is asking for guidance on how to approach part (e) and suggests starting by writing down the problem statement, given facts, and relevant definitions.
  • #1
ashah99
60
2
Homework Statement
Please see below from problem statement
Relevant Equations
Ergodicity: ensamble mean = time average mean
Hello all, I have a random sequences question and I am mostly struggling with the last part (e) with deriving the marginal pdf. Any help would be greatly appreciated.
My attempt for the other parts a - d is also below, and it would nice if I can get the answers checked to ensure I'm understanding things properly or if I’m off track.

Problem
D8375821-5DB2-4EBB-8847-3DBE44D6EBCA.jpeg

Attempt
For part (a) I got yes, because the mean is 0 (constant) and the autocorrelation function is independent of time k. I got Rx(m) = 0.5*cos(0.2*pi*m)
For (b) I said yes because all statistics are not dependent on time k.
For (c) both the ensemble and time averages would be 0, and since these are equal it seams yes, Xk is ergodic in the mean.
For (d), I believe it is no, because the autocorrelation function is a periodic sinusoid and goes on infinitely, so the limit as Rx(m) goes to infinity does not exist, i.e. it is not constant and not equal to mu ^2
 
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  • #2
What work have you done on part (e)? Have you set up the problem on paper?

Often, just writing down the problem statement, the given facts, and the relevant definitions gives you a good idea of where to start.
 

1. What are sinusoidal sequences with random phases?

Sinusoidal sequences with random phases are a type of signal that is characterized by a sinusoidal waveform with varying phases. The phases are randomly distributed, meaning they are not predictable and can change from one sample to the next.

2. How are sinusoidal sequences with random phases generated?

Sinusoidal sequences with random phases are typically generated using a random number generator. The amplitude, frequency, and phase of the sinusoidal waveform are kept constant, while the phase is varied randomly for each sample.

3. What are the applications of sinusoidal sequences with random phases?

Sinusoidal sequences with random phases have various applications in signal processing, such as in noise reduction, channel equalization, and channel estimation. They are also used in cryptography for generating random numbers.

4. How are sinusoidal sequences with random phases different from other types of signals?

Unlike other types of signals, sinusoidal sequences with random phases have a random phase component, which makes them more unpredictable and less susceptible to interference. They also have a wider frequency spectrum, making them useful for applications that require a broad range of frequencies.

5. Can sinusoidal sequences with random phases be used in real-world systems?

Yes, sinusoidal sequences with random phases have been used in various real-world systems, such as wireless communication, radar systems, and audio signal processing. They have been proven to be effective in improving signal quality and reducing interference in these systems.

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