Convolutions, Polynomials and Flipped Kernels

  • My favourite use case for this: By the same derivation as this blog, one can prove that, if you have any two probability distributions X and Y (they can be different), the probability distribution of X+Y is a convolution of the PMFs/PDFs of X and Y.

  • Beware - one step more and you get into the region of generating functions. I recommend a book Herbert Wilf with a wonderful name of Generatingfunctionology (https://www2.math.upenn.edu/~wilf/gfology2.pdf).

  • You can also multiply polynomials by way of analogy with integer multiplication:

             3  1  2  1
           ×    2  0  6
           ------------
            18  6 12  6
          0  0  0  0
       6  2  4  2
      -----------------
       6  2 22  8 12  6
    
    = 6x^5 + 2x^4 + 22x^3 + 8x^2 + 12x^1 + 6x^0.

  • The visualizations make the concept easy to grasp.

  • This and complex analysis are fascinating topics in Undergraduate studies.

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