Good robot performance often relies upon the selection of design parameters that lead to a well conditioned Jacobian or impedance " design " matrix. In this paper, a new design matrix normalization technique is presented to cope with the problem of non-homogeneous physical units. The technique pre and post-multiplies a design matrix by diagonal scaling matrices corresponding to the range of joi...

In several online prediction problems of recent interest the comparison class is composed of matrices with bounded entries. For example, in the online max-cut problem, the comparison class is matrices which represent cuts of a given graph and in online gambling the comparison class is matrices which represent permutations over n teams. Another important example is online collaborative filtering...

The problem of finding a diagonal similarity scaling to minimize the scaled singular value of a matrix arises frequently in robustness analysis of control systems. It is shown here that the set of optimal diagonal scalings is nonempty and bounded if and only if the matrix that is being scaled is irreducible. For an irreducible matrix, a sufficient condition is derived for the uniqueness of the ...

In this paper we use the Moore-Penrose inverse in the case of a close to singular and ill-conditioned, or singular variance-covariance matrix, in the classic Portfolio Selection Problem. In this way the possible singularity of the variance-covariance matrix is tackled in an efficient way so that the various application of the Problem to benefit from the numerical tractability of the Moore-Penro...

In many applications that work on huge data sets, from areas like bioinformatics, data-mining, network analysis, optimization, and simulation, the computation time is a major concern. To shorten this time, we have to take into account the many aspects that determine the running time of a program on a modern computer. One of these aspects is the range of different type of memory, from fast but s...

Optimal conditions are used in nondynamical formalism to diagonalize the pionproton reaction matrix as much as possible. Invariance laws are imposed to simplify the relationship between observables and bilinear combination of amplitudes. Transverse amplitudes are determined by using measured polarization parameter in xfp elastic scattering at 6.0 GeVIC

We study the optimal and superoptimal Frobenius operators in a general matrix vector space and in particular in the multilevel trigonometric matrix vector spaces, by emphasizing both the algebraic and geometric properties. These general results are used to extend the Korovkin matrix theory for the approximation of block Toeplitz matrices via trigonometric vector spaces. The abstract theory is t...

Compressed sensing is a promising technique that attempts to faithfully recover sparse signal with as few linear and nonadaptive measurements as possible. Its performance is largely determined by the characteristic of sensing matrix. Recently several zero-one binary sensing matrices have been deterministically constructed for their relative low complexity and competitive performance. Considerin...

Optimal load balancing in sparse matrix decomposition without disturbing the row/column ordering is investigated. Both asymptotically and run-time efficient exact algorithms are proposed and implemented for one-dimensional (1D) striping and two-dimensional (2D) jagged partitioning. Binary search method is successfully adopted to 1D striped decomposition by deriving and exploiting a good upper b...