Lines Matching full:a_1
510 // y = a_1 exp(b_1 x) + a_2 exp(b_3 x^2 + c_1)
513 // a_1, a_2, b_1, b_2, and c_1.
515 // Notice here that the expression on the left is linear in a_1
518 // values of a_1 and a_2. Indeed, its possible to analytically
519 // eliminate the variables a_1 and a_2 from the problem all
538 // computed for the whole problem (a_1, a_2, b_1, b_2, c_1) and
539 // additional optimization step is performed to estimate a_1 and
543 // linear in a_1 and a_2, i.e., Solve for the trust region step
545 // further optimize just a_1 and a_2. For the linear case, this
547 // non-linear problems, any method for solving the a_1 and a_2
548 // optimization problems will do. The only constraint on a_1 and
552 // (a_1, a_2), but decomposing the graph corresponding to the
