Hi
I guess the Wikipedia page is more than complete:
http://en.wikipedia.org/wiki/Principal_component_analysisBut if you like to hear it simple, it is just a 3 step process (for n dimensional data matrix):
1- Perform the singulat value decomposition on your data, this will give you eigenvectors v and eigenvalues lambda
2- Sort eigenvectors regarding their corresponding eigenvalue in descending fashion
3- Choose the m top vectors (m<n), those will be your principle component vectors (the vectors can best describe your data in their direction)