Open AccessThe generalized convolution formula and its application are discussed
Author(s) -
Yinshan Jiang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1827/1/012076
Subject(s) - convolution (computer science) , convolution power , mathematics , function (biology) , convolution theorem , distribution (mathematics) , generalized function , convolution of probability distributions , circular convolution , random variable , variable (mathematics) , computer science , calculus (dental) , pure mathematics , mathematical analysis , moment generating function , statistics , fourier transform , artificial intelligence , evolutionary biology , medicine , fourier analysis , dentistry , artificial neural network , fractional fourier transform , biology
There are two ways to find the distribution of two-dimensional random variable function: distribution function method and convolution formula method, the distribution function method is too large; calculation is easy to make mistakes, the convolution formula method has limitations must be independent, Now let’s introduce the generalized convolution formula, The generalized convolution formula does not require independent constraints and can simplify the operation.