The robust disturbance rejection bounds in [11 are tight with respect to the disturbance set that has a specified L , norm bound. This note shows that the robust disturbance rejection bounds in [11 are also tight with respect to a weighted L , disturbance set that has a specified bound on its outer product by choosing a special weight matrix in the L , norm. The matrix can be computed by numeri...

The minimization of roundoff noise subject to l2-norm dynamic-range scaling constraints in two-dimensional (2-D) state-space digital filters is considered by using joint error feedback and coordinate transformation optimization. An iterative approach for minimizing the roundoff noise under l2-norm dynamic-range scaling constraints is developed by jointly optimizing a scalar error-feedback matri...

The singular value decomposition and spectral norm of a matrix are ubiquitous in numerical analysis. They are extensively used in proofs, but usually it is not necessary to compute them. However, there are some important applications in the realm of verified error bounds for the solution of ordinary and partial differential equations where reasonably tight error bounds for the spectral norm of ...

The issue of Cα-degree reduction of triangular Bézier surfaces is exposed. It is anticipated that both triangular Bézier surfaces are Cα-continuous at the vertices. The Euclidean norm as well as the L2−norm is used. The final solutions are given in terms of the matrix of degree raising, the Gram matrix, and the Bézier points. Moreover, it is shown that the solutions using both norms are equival...

In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...

There is growing body of learning problems for which it is natural to organize the parameters into matrix, so as to appropriately regularize the parameters under some matrix norm (in order to impose some more sophisticated prior knowledge). This work describes and analyzes a systematic method for constructing such matrix-based, regularization methods. In particular, we focus on how the underlyi...

A b g r a a A simultaneous H2/H® control problem is considered. This problem seeks to minimize the H 2 norm of a closed-loop transfer matrix while simultaneously satisfying a prescribed H~ norm bound on some other closed-loop transfer matrix by utilizing dynamic state feedback controllers. Such a problem was formulated earlier by Rotea and Khargonekar (Automatica, 27, 307-316, 1991) who conside...

(including the generalized coupled Sylvester matrix equations as special cases) have numerous applications in control and system theory. In this paper, an iterative algorithm is constructed to solve the general coupled matrix equations and their optimal approximation problem over generalized reflexive matrix solution (X1,X2, . . . ,Xq). When the general coupled matrix equations are consistent o...

Covariance matrix plays a central role in multivariate statistical analysis. Significant advances have been made recently on developing both theory and methodology for estimating large covariance matrices. However, a minimax theory has yet been developed. In this paper we establish the optimal rates of convergence for estimating the covariance matrix under both the operator norm and Frobenius n...