A convolution of a convolution

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In summary, the conversation discusses the concept of convolutions and provides an example of how to calculate them. The conversation then delves into the idea of a convolution of a convolution, which is represented by the equation (h*(f*g))(t). The summary concludes by explaining how this equation would look like in mathematical terms.
  • #1
thrillhouse86
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Hi,
can someone please give me an example of what a convolution of a convolution would look like ?

Thanks
 
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  • #2
What do you mean by "look like"?
 
  • #3
as in:
[tex]
f*g = \int^{\infty}_{-\infty} f(\tau)g(t-\tau) d\tau
[/tex]

what would
h*(f*g) look like ?

-Thrillhouse
 
  • #4
I should think something along these lines:

[tex](f*g)(t) \stackrel{\mathrm{def}}{=} \displaystyle\int_{-\infty}^\infty f(x)g(t - x) dx[/tex]

[tex](h*(f*g))(t) = \displaystyle\int_{-\infty}^\infty h(y)(f*g)(t - y) dy = \displaystyle\int_{-\infty}^\infty h(y) \left( \displaystyle\int_{-\infty}^\infty f(x)g(t - y - x) dx \right) dy[/tex]
 
  • #5
thanks pbandjay
 

1. What is a convolution of a convolution?

A convolution of a convolution, also known as a double convolution, is a mathematical operation that combines two convolutions together. It is a way of applying two filters consecutively to a signal or image, resulting in a new and more refined output.

2. How is a convolution of a convolution calculated?

To calculate a convolution of a convolution, you first convolve the input signal/image with the first filter, and then convolve the resulting output with the second filter. This involves multiplying the filter values with the corresponding signal/image values and summing them up, similar to a regular convolution operation.

3. What is the purpose of a convolution of a convolution?

The purpose of a convolution of a convolution is to enhance and refine the features of a signal or image. By applying multiple filters in succession, it is possible to extract more complex and detailed information from the input data.

4. Can a convolution of a convolution be applied to any type of data?

Yes, a convolution of a convolution can be applied to any type of data that can be represented as a signal or image. This includes audio signals, time series data, and 2D/3D images.

5. What are some real-world applications of a convolution of a convolution?

A convolution of a convolution has various applications in fields such as image processing, computer vision, and signal processing. It is commonly used for tasks such as edge detection, feature extraction, and denoising in medical imaging, satellite imagery, and video processing.

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