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This is convex and is known as the quadrature matrix programming problem.
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Note that the optimization problems and can also be solved first by reformulating them as quadratic matrix programming [25] problems and then applying the semidefinite programming (SDP) relaxation technique.
This matrix arises from a linear programming problem.
Tyndall [1, 2] treated rigorously a continuous-time linear programming problem with the constant matrices, originating from the 'bottleneck problem' proposed by Bellman [3].
The validation algorithm works by finding solutions to a linear programming problem involving these vectors and matrices.
Affine registration problem can be simplified to a quadratic programming problem by transforming the affine transform matrix as exponential mappings of lie group and their Taylor approximations.
Among all feasible filters, the one minimizing a guaranteed H2 cost of the estimation error is determined by a pure convex programming problem, expressed in terms of linear matrix inequalities (LMIs).
Then, the algorithm to unconstrained problem is combined with the dynamic programming method to solve the linearly constrained binary quadratic programming problem with Q being a five-diagonal matrix (LCBQP5).
For a given N, if the Hessian matrix (mathbf{H}_{N}) is strictly positive definite, the quadratic programming problem (25) is well posed and can be solved in polynomial time [27].
In the proposed approach, the mismatch vector of the desired steering vector is estimated by solving a quadratically constrained quadratic programming problem using an interference-plus-noise subspace projection matrix.
For the asymmetric CCEiCP (where at least one of the matrices A or B is asymmetric), we will formulate another nonlinear programming problem in the next section.
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