Sentence examples for matrices using linear from inspiring English sources

The total entropy and noise entropy were then obtained from the response matrices using linear extrapolation with the following parameters: size = 5/10, 6/10,..,10/10 of data; ν = 8, 9,..,17 voltage levels; T−1 = 3, 4,..,6 points.

Nonnegative matrix factorization (NMF) approximates a given data matrix using linear combinations of a small number of nonnegative basis vectors, weighted by nonnegative encoding coefficients.

Although the first-order AR model is just an approximation to the actual statistics of the random radio propagation process, it is more realistic than those models assuming constant channel parameters (identity matrix) or using linear interpolation.

These TNs enable to further reduce the data size by using optimization-based algorithms to find factor matrices and optimize using linear and nonlinear least square methods.

Using linear matrix inequality approach and introducing some free matrices, sufficient criterion is established to guarantee the admissibility and DR-stability of the considered class of nonlinear systems.

Then, a residual feedback control law is given for compensating the influence of fault and the parameter matrices of the controller are obtained by solving a non-convex optimization problem using linear matrix inequality (LMI) technique.

An explicit procedure is described which shows how a Lyapunov matrix, which satisfies both a discrete Riccati inequality and a structural constraint, can be obtained using Linear matrix inequality optimization.

The computation of the gain matrix is formulated in terms of a static output feedback problem, which can be efficiently solved using linear matrix inequalities.

The problem is solved using Linear Matrix Inequalities (LMI).

The sufficient conditions are obtained by using linear matrix inequality (LMI) techniques.

All the three methods are based on the convex optimization framework using linear matrix inequalities (LMIs).