How Does Normality Arise in the Output of an LTI System with Normal Noise Input?

Your Name]In summary, the central limit theorem can be used to show that no(Ts) has a normal distribution with mean zero and variance (η/2)Es. This is because the signal s(t) can be considered as a sum of many small segments, each with a normal distribution, and the properties of LTI systems ensure that the output will also have a normal distribution.
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asmani
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Homework Statement



The signal s(t) is a deterministic signal with the finite duration (0,Ts) and the energy Es=∫s2(t)dt. In the following system, n(t) is a normal noise with the mean zero and the power spectral density Gn(f)=η/2. Show that no(Ts) has a normal distribution with the mean zero and the variance (η/2)Es.

attachment.php?attachmentid=45954&stc=1&d=1333791495.png

Homework Equations



E[no(t)]=H(0)E[n(t)]

Rnono(τ)=h(τ)*h(-τ)*Rnn(τ)
(* is the convolution)

var(no(t))=Rnono(0)=∫Gno(f)df
(since E[no(t)]=0)

Gno(f)=|H(f)|2Gn(f)

The Attempt at a Solution



I know how to derive mean and variance , but don't know how to show normality. The prof just mentioned in the class that if the input to a LTI system is normal, then the output is so. How to prove this?

Thanks in advance.
 

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Dear poster,

Thank you for your question. To show that no(Ts) has a normal distribution with the mean zero and the variance (η/2)Es, we can use the central limit theorem. This theorem states that the sum of a large number of independent and identically distributed random variables will be approximately normally distributed, regardless of the distribution of the individual variables.

In this case, we can consider the signal s(t) to be composed of an infinite number of small segments, each with duration Ts. Each of these segments can be seen as a random variable with a normal distribution, since it is a deterministic signal with finite duration. Therefore, by the central limit theorem, the sum of these segments, which is no(Ts), will also have a normal distribution.

Furthermore, since n(t) is a normal noise with mean zero and power spectral density Gn(f)=η/2, we can use the properties of LTI systems to show that the output of the system, no(Ts), will also have a normal distribution with mean zero and variance (η/2)Es. This is because the output of an LTI system is the convolution of the input with the impulse response, which in this case is n(t). Since n(t) is a normal noise, the output will also be normal.

I hope this helps to answer your question. If you have any further questions or need clarification, please don't hesitate to ask. Good luck with your studies!
 

FAQ: How Does Normality Arise in the Output of an LTI System with Normal Noise Input?

What is a LTI system?

A LTI (linear time-invariant) system is a type of system used in signal processing and control theory. It is characterized by its linearity, meaning that its output is directly proportional to its input, and time-invariance, meaning that its behavior does not change over time.

What is considered a normal input to a LTI system?

A normal input to a LTI system is a signal that is continuous in time and has finite energy or power. This includes signals such as sinusoidal waves, step functions, and impulse functions.

How does a LTI system respond to a normal input?

A LTI system responds to a normal input by applying a mathematical operation to the input signal, resulting in an output signal. The specific response of the system depends on its characteristics and the properties of the input signal.

Can a LTI system process non-normal inputs?

Yes, a LTI system can process non-normal inputs, but the resulting output may not be meaningful. Non-normal inputs, such as signals with infinite energy or power, can cause the system to behave in unexpected ways or even become unstable.

What are some examples of LTI systems?

Some examples of LTI systems include electronic filters, audio equalizers, and electrical circuits. LTI systems are also commonly used in signal processing applications, such as image and audio processing.

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