Coarse grain parallelism inherent in the solution of Linear Programming LP problems with block angular constraint matrices has been exploited in recent research works However these approaches su er from unscalability and load imbalance since they exploit only the exist ing block angular structure of the LP constraint matrix In this paper we consider decomposing LP constraint matrices to obtain ...

This paper presents an approach for stiffness modelling of the lower mobility parallel manipulators using the generalized Jacobian. The approach can be implemented by two steps:(1) The first order deflection analysis by decomposing twist space of the end-effector into a pair of complementary twist subspaces associated with the permitted and restricted instantaneous motions, (2) The kinestatic a...

The paper introduces an approach for crosstalk-free bitpermute-complement (BPC) permutations routing in hybrid optical variable-stage shuffle-exchange networks (SENs) of size where N=2, and the number of stages can vary in . The number of stages should be asserted as required by a given BPC permutation for its admissibility. The crosstalk is caused by interacting of two optical signals within t...

Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and non-negative matrix factorization. We then give a simple yet efficient multiplicative algorithm for finding the optimal values of the hidden components...

We consider the source separation problem for single-channel music signals. After a brief review of existing methods, we focus on decomposing a mixture into components made of harmonic sinusoidal partials. We address this problem in the Bayesian framework by building a probabilistic model of the mixture combining generic priors for harmonicity, spectral envelope, note duration and continuity. E...

Absfract-A straightforward method is presented for the determination of the optimal sensor exploration in the localization of a polyhedral object, whose geometry is known. Optimality is intended in the sense of the a posteriori covariance matrix of the object position and orientation parameters. The method consists in decomposing the problem into simpler subproblems, eachone relative to a singl...

The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is investigated. By decomposing some connection weight matrices, new Lyapunov-Krasovskii functionals are constructed, and serial new improved stability criteria are derived. These criteria are formulated in the forms of linear matrix inequalities LMIs . Compared with some previous results, the new ...

The problem of robust stability analysis for uncertain discrete singular time-delay systems is investigated in this paper. By decomposing the nominal system into slow and fast subsystems, a linear matrix inequality (LMI) condition is proposed for a discrete singular time-delay system to be regular, causal and stable. Based on this, an LMI criterion is obtained for robust stability of an uncerta...