Understanding Growth Order of Functions in Integral Equations

In summary, the conversation discusses an integral equation with a positive kernel. If h(x) is bounded by x^a and the integral of K(y)y^a exists and is a positive real number, then f(x) is also bounded by x^a. This is shown by a change of variable and the use of F(t) = f(t)/t^a. However, it is noted that F could still tend to infinity slower than K(z)z^(a-1) and the equation would still hold.
  • #1
zetafunction
391
0
let be the integral equation

[tex] h(x)= \int_{0}^{\infty} \frac{dy}{y}K(y/x)f(y) [/tex]

here the kernel is always a positive , then if [tex] h(x)=O(x^{a}) [/tex] and the integral


[tex] \int_{0}^{\infty} \frac{dy}{y}K(y)y^{a} [/tex] exists and is a positive real number then also [tex] f(x)= O(x^{a}) [/tex]
 
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  • #2
zetafunction said:
let be the integral equation

[tex] h(x)= \int_{0}^{\infty} \frac{dy}{y}K(y/x)f(y) [/tex]

here the kernel is always a positive , then if [tex] h(x)=O(x^{a}) [/tex] and the integral


[tex] \int_{0}^{\infty} \frac{dy}{y}K(y)y^{a} [/tex] exists and is a positive real number then also [tex] f(x)= O(x^{a}) [/tex]
I'll restrict to positive x as the negative case can be tackled similarly.
With a change of variable y/x =z , we get
[tex] \frac{h(x)}{x^{a}} = \int_{0}^{\inftz} \frac{dz}{z}K(z)z^{a}F(xz)[/tex]

where F(t) =f(t) /t^a. As [tex] h(x)=O(x^{a}) [/tex] , the right hand side is bounded,O(1).
I don't see why F =O(1) . F could tend to infinity much slower than
[tex] K(z)z^{a -1}[/tex] & the first equation could still hold.
 

What is the growth order of function?

The growth order of function, also known as the asymptotic growth rate, refers to the rate at which a function increases as its input increases. It is typically represented by the Big O notation and is used to describe the limiting behavior of a function.

How is the growth order of function calculated?

The growth order of function is calculated by looking at the dominant term in the function's equation. This dominant term is typically the term with the highest power. The coefficient of this term is then ignored, and the remaining term is used to represent the growth order of the function.

Why is the growth order of function important?

The growth order of function is important because it allows us to compare the efficiency of different algorithms or functions. By understanding the growth order, we can determine which function will perform better for larger inputs and make informed decisions in terms of time and space complexity.

What are the different types of growth orders?

There are several types of growth orders, including constant, logarithmic, linear, quadratic, exponential, factorial, and more. These growth orders are arranged in increasing order of efficiency, with constant being the most efficient and factorial being the least efficient.

Can the growth order of a function change?

Yes, the growth order of a function can change depending on the input size. For example, a function may have a linear growth order for smaller inputs but a quadratic growth order for larger inputs. It is essential to consider the worst-case scenario when analyzing the growth order of a function.

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