52 results about "Linear matrix inequality" patented technology

In convex optimization, a linear matrix inequality (LMI) is an expression of the form LMI(y):=A₀+y₁A₁+y₂A₂+⋯+yₘAₘ⪰0 where y=[yᵢ , i = 1,…,m] is a real vector, A₀,A₁,A₂,…,Aₘ are n×n symmetric matrices 𝕊ⁿ, B⪰0 is a generalized inequality meaning B is a positive semidefinite matrix belonging to the positive semidefinite cone 𝕊₊ in the subspace of symmetric matrices 𝕊. This linear matrix inequality specifies a convex constraint on y.