datahead8888

Hello, Background: I was going to implement an implicit approach to 3d tetrahedra deformations (first in Matlab then in C++). I need the Jacobian for the partial derivative of force wrt position to do this. I found this paper that gives a method for computing it: http://www-bcf.usc.edu/~jbarbic/Barb...nessMatrix.pdf The Question: In the report, he defines a 2skew function (to the right of the page). I'm pretty confused on what it means. I think I forgot what skew means from linear algebra - that's probably part of my problem. It sounds like skew symmetric means that a negated matrix is equal

The y variables would be treated as constants wrt the partial derivative. They would change throughout the course of the C++ program that uses this and would be plugged into the resulting Jacobian structure.

Suppose we have a function consisting of a series of matrices multiplied by a vector: f(X) = A * B * b --where X is a vector containing elements that are contained within A, b, and/or b, --A is a matrix, B is a matrix, and b is a vector Each Matrix and the vector is expressed as more terms, ie... X = (x1, x2, x3) A = [ x1 + y1 y4 y7 ] [ y2 x2 + y5 y8 ] ] y3 y6 x3 + y9 ] B = [ y1 x2 + y4 x3 + y7 ] [x1 + y2 y5 y8 ] ] y3 y6 y9 ] b = [y1 y2 y3]' (' means transposed) Now we want to find the Jacobian of f - ie the p