Using SDPs to design approximation algorithms. positive semidefinite
... Using SDPs to design approximation algorithms. Symmetric n×n matrix M with real entries is positive semidefinite (psd) if it can be represented as M =AT A for some n×n matrix A. Thinking of the columns of A as n-dim vectors u1, u2,.., un, we see that (i, j) entry of M is M(i, j) = ui· uj . General f ...
... Using SDPs to design approximation algorithms. Symmetric n×n matrix M with real entries is positive semidefinite (psd) if it can be represented as M =AT A for some n×n matrix A. Thinking of the columns of A as n-dim vectors u1, u2,.., un, we see that (i, j) entry of M is M(i, j) = ui· uj . General f ...
Introduction to Systems and General Solutions to Systems
... If the n solutions form a fundamental set of solutions (in other words, if the yi are linearly independent solutions), then we call Ψ a fundamental matrix for the system. We have already seen that any solution to the system y′ = P (t)y must have the form Ψ(t)c where Ψ(t) is our fundamental matrix a ...
... If the n solutions form a fundamental set of solutions (in other words, if the yi are linearly independent solutions), then we call Ψ a fundamental matrix for the system. We have already seen that any solution to the system y′ = P (t)y must have the form Ψ(t)c where Ψ(t) is our fundamental matrix a ...
