How to rewrite 2D Gaussian eqn in terms of x?

In summary, the conversation discusses rewriting a 2D Gaussian equation in terms of x and the possibility of solving for x alone. It is noted that the equation is already written in terms of both x and y and cannot be rewritten in terms of x only. The concept of solving for x is further explored, with the idea that a specific value for y could be assumed and then x could be solved for. The use of a constant \sigma is mentioned and it is stated that x can be solved for given a specific value for y and the function f(x,y). The equation ln\left(\frac{f(x,y)}{A}\right)=\frac{(x-x_0)^2}{2\sigma_x^2}+\
  • #1
ireland01
17
0
http://upload.wikimedia.org/math/1/9/8/1983171154842b0b061fc42aa5eb7642.png"

How to rewrite this 2D Gaussian eqn in terms of x?
i need to calculate the x and y values.
let x0=0 and y0=0.

is it complex?
 
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  • #2
What do you mean by "write in terms of x"? It is already written in terms of x and y and cannot be written in terms of x only.

Do you mean "solve for x"? Again, because it is a function of both x and y, you cannot solve it for x alone. You can assume a specific value for y and then solve for x.

But to "solve for x" you would also have to have a specific value of f(x,y).

I simply don't understand what you mean by "calculate the x and y values". In general, x and y can have any real values. What conditions are you placing on f(x,y) to give specific x and y values that you could calculate?
 
  • #3
yes sorry i mean solve for x

let f(x,y) = y = 2. say
 
  • #4
I've never seen [itex]\sigma[/itex] so assuming it's to be treated as a constant, yes you certainly can solve for x given y and f(x,y). It's relatively simple too.

[tex]-ln\left(\frac{f(x,y)}{A}\right)=\frac{(x-x_0)^2}{2\sigma_x^2}+\frac{(y-y_0)^2}{2\sigma_y^2}[/tex]

It should be obvious from here how to solve for x.
 

1. What is the 2D Gaussian equation?

The 2D Gaussian equation, also known as the bivariate normal distribution, is a mathematical function that describes the distribution of a two-dimensional random variable. It is often used in statistics and probability to model natural phenomena.

2. How is the 2D Gaussian equation typically written?

The 2D Gaussian equation is typically written as: f(x,y) = (1/2πσ^2)e^-(x^2+y^2)/2σ^2 where σ is the standard deviation and (x,y) are the coordinates of the point in the distribution.

3. Why would someone want to rewrite the 2D Gaussian equation in terms of x?

Rewriting the 2D Gaussian equation in terms of x can make it easier to analyze and work with the distribution, as it allows for the separation of the two variables. This can be especially useful in applications where the x variable is of more interest than the y variable.

4. How can the 2D Gaussian equation be rewritten in terms of x?

The 2D Gaussian equation can be rewritten in terms of x by using the standard formula for converting from polar to Cartesian coordinates. This results in the equation: f(x) = (1/√(2πσ^2))e^-(x^2)/2σ^2 where x is the independent variable and all other terms remain the same.

5. Are there any limitations to rewriting the 2D Gaussian equation in terms of x?

Yes, there are limitations to rewriting the 2D Gaussian equation in terms of x. This method assumes that the x and y variables are independent, which may not always be the case in real-world scenarios. Additionally, some information about the distribution may be lost when transforming it into a one-dimensional form.

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