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The criteria are expressed as a set of linear matrix inequalities, which can be easily examined using standard numerical software.
Since these conditions involve matrix equalities, the cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem subject to linear matrix inequalities, which can be readily solved by using standard numerical software.
Different from the traditional quadratic framework, the synthesis problem is solved by exploiting the cone complementarity linearization (CCL) method, together with a sequential minimization problem subject to LMI constraints obtained for the existence of admissible controllers, which can be readily solved by using standard numerical software.
Combining with capturing the characteristic of sampled-data systems with a novel piecewise Lyapunov Krasovskii functional (LKF), a less complex and less conservative H∞ stabilization criterion is formulated as linear matrix inequalities (LMIs), which can be easily checked by using standard numerical software.
Based on matrix inequality formulation with a fixed parameter, the proposed learning law can be designed by solving two matrix inequalities, which can be checked easily using standard numerical software [27, 28].
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The numerical solution of these equations is straight-forward using standard numerical techniques.
Patchy patterns were computed using standard numerical methods on a regular grid.
The derived criteria are expressed in terms of linear matrix inequalities that can be easily checked by using the standard numerical software.
The l 2 -gain performance index can characterize the disturbance attenuation property of the underlying systems, and then, based on the established stability results, delay-dependent sufficient conditions for the existence of l 2 -gain performance are derived in terms of LMIs, which can be easily verified by using some standard numerical software.
The proposed conditions are easily and numerically tractable via standard numerical software.
Radiation dosimetry estimates were calculated using standard OLINDA/EXM software.
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