How to apply Gradient Descent to a summ of function My target is to find a center of a circle that approximate a set of dots

i want to find minimum of a function:
$$\sum_{i=0}^N (\sqrt{(x_i - a)^2 + (y_i - b)^2} - R)^2$$

this function represent an error of a my approximation of a set a dots on a plane with a circle.

I did a bit of a googling and find that Gradient Descent is a decent method for a numerical searching for a minimum of function.

But i have a trouble with understanding how i should correcnt my A,B,R with partial derrivative, when i have function of summ.

picture related for better explanation of my problem:
http://imgur.com/gallery/ecUdXnB
I came up with the simple answer after I just rewrite this idea on paper:

$$\frac{\delta \sum \Big[f(x,y)\Big]}{\delta x}  = \sum \frac{\delta f(x,y)}{\delta x}$$

so it's just partial derivative for each Experimental Dot summed.
Algo works quite well.