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In order to reduce the computational load of the recursive least squares (RLS) algorithm, a decomposition based least squares algorithm is developed for non-uniformly sampled multirate systems. The main ideal is to decompose the identification model of the non-uniformly sampled systems into several submodels with smaller dimensions and fewer parameters based on the hierarchical identification principle...
In this paper, we present a general family of iterative methods to solve linear equations, which includes the well-known Jacobi and Gauss-Seidel iterations as its special cases. We give the necessary and sufficient conditions for convergence of the iterative solutions. Furthermore, the methods are extended to solve coupled Sylvester matrix equations. In our approach, we regard the unknown matrices...
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