Probability density function of digital filter

In summary, the pdf of y(n) can be obtained by convolving the pdf's of x(n) and x(n-1), which will result in a gamma distribution with parameters (2,1). This is because y(n) is the sum of two independent variables, and the pdf of a sum of two independent variables can be obtained by convolution. The corrected formula for y(n) is y(n) = x(n)^2 + x(n-1)^2, and the resulting pdf will still be a gamma distribution with parameters (2,1).
  • #1
purplebird
18
0
given that x has an exponential density function ie p(x) = exp (-x) and x(n) & x(m) are statistically independent.

Now y(n) = x(n-1)+x(n)

what is the pdf (probability density function) of y(n)
 
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  • #2
purplebird said:
given that x has an exponential density function ie p(x) = exp (-x) and x(n) & x(m) are statistically independent.

Now y(n) = x(n-1)+x(n)

what is the pdf (probability density function) of y(n)

The pdf of a sum of two independent variables can be obtained by the convolution of their respective pdf's.
 
  • #3
Y(n) will be distributed as gamma(2,1) if X(n) has the pdf exp[-x(n)].
 
  • #4
I made a mistake while typing up the question :

y(n) = [x(n-1) + x(n)]^2

so

y(n) = x(n)^2 + x(n-1)^2

So is the pdf of y(n) convolution of exp(-x(n)^2) and exp(-x(n-1)^2)

Thanks
 

FAQ: Probability density function of digital filter

What is a probability density function (PDF) in the context of digital filters?

A probability density function (PDF) is a mathematical function that describes the relative likelihood of a random variable taking on a specific value. In the context of digital filters, the PDF represents the distribution of the values that the filter outputs in response to a given input signal. It is often used to analyze the performance and behavior of digital filters in various applications.

How is the PDF of a digital filter determined?

The PDF of a digital filter is determined by the design and characteristics of the filter, such as its transfer function, order, and coefficients. It can also be influenced by the input signal and any noise or disturbances present in the system. The PDF can be calculated analytically or through simulations and experiments.

What is the significance of the PDF in digital filter analysis?

The PDF provides valuable information about the behavior and performance of a digital filter. It can reveal important characteristics, such as the filter's frequency response, passband and stopband ripple, and attenuation. The PDF can also be used to evaluate the filter's stability, linearity, and other properties.

How does the shape of the PDF affect the performance of a digital filter?

The shape of the PDF can have a significant impact on the performance of a digital filter. For example, a narrow and tall PDF indicates a smaller spread of output values, which may result in a more precise and accurate response. On the other hand, a wider and flatter PDF may indicate a larger spread of output values, which can lead to more errors and distortions in the filter's output.

Can the PDF be used to optimize or improve the performance of a digital filter?

Yes, the PDF can be used to optimize or improve the performance of a digital filter. By analyzing the PDF, engineers can identify areas where the filter may be underperforming or exhibiting unwanted behaviors. This information can be used to make design modifications or adjustments to the filter's parameters, ultimately leading to a better performing filter.

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