It is effective to model the corrupted signals with probability theories and statistic….

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MENC5013 Advanced Digital Signal Processing

Tutorial 1:

Signals are frequently corrupted with additive noise. It is effective to model the corrupted signals with probability theories and statistic.

  1. What is the relationship between probability distribution function and probability density function (p.d.f)?
  1. Mean and standard diviation are two major statistical measurements used in determaining the characteristic of the additive noise. Clearly explain the process of deriving mean and standard deviation from their p.d.f?
  1. Uniform white noise and Gaussian white noise are two common approaches used to model the characteristic of additive noise. Clearly explain the process of deriving mean and standard deviation from their respective p.d.f?
  1. Sketch the p.d.f of Uniform white noise and Gaussian white noise. What is the effect on their graph with respect to the change of mean and standard deviation?
  1. Please use the function provided in matlab to plot the answers in (d)?
  1. Average power of the additive noise is also an interesting parameter in noise modeling. Please explain how the average power of the noise can be approximated from the p.d.f?
  1. Please provide a suitable example of using the Uniform white noise to model an additive noise.
  1. Please provide a suitable example of using the Gaussian white noise to model an additive noise?

K.C. Lim 2010

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MENC5013 Advanced Digital Signal Processing Tutorial 1: Signals are frequently corrupted with additive noise. It is effective to model the corrupted signals with probability theories and statistic. What is the relationship between probability distribution function and probability density function (p.d.f)? Mean and standard diviation are two major statistical measurements used in determaining the characteristic of the additive noise. Clearly explain the process of deriving mean and standard deviation from their p.d.f? Uniform white noise and Gaussian white noise are two common approaches used to model the characteristic of additive noise. Clearly explain the process of deriving mean and standard deviation from their respective p.d.f? Sketch the p.d.f of Uniform white noise and Gaussian white noise. What is the effect on their graph with respect to the change of mean and standard deviation? Please use the function provided in matlab to plot the answers in (d)? Average power of the additive noise is also an interesting parameter in noise modeling. Please explain how the average power of the noise can be approximated from the p.d.f? Please provide a suitable example of using the Uniform white noise to model an additive noise. Please provide a suitable example of using the Gaussian white noise to model an additive noise? K.C. Lim 2010

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