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A unified framework is established to solve the addressed H∞ filtering problem by exploiting linear matrix inequality (LMI) approach.
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The expectation derivation in (23) is based heavily on exploiting linear-algebraic concepts and the properties of matrix permanents.
By exploiting the dissimilarity matrix, we merge similar vessel type classes using a threshold.
In this study, we extrapolate the performance to by exploiting the linear relation between and.
With this realization, they sought to mathematically reverse the effects of network convolution, by exploiting key properties of matrix decomposition and infinite sums.
The gain matrices of the FUIO are obtained by solving linear matrix inequalities.
The design is described by matrix inequalities, which can be efficiently solved by the linear matrix inequality toolbox in Matlab.
The estimator gain matrix can be obtained by solving linear matrix inequalities (LMIs).
Stability analysis is performed by using switched Lyapunov functions and formulated by linear matrix inequalities (LMI).
The designed conditions are given by linear matrix inequalities (LMIs).
In all cases, the gain matrices are determined by linear matrix inequality approach.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com