Kojima, Shindoh and Hara proposed a family of search directions for the semidefinite linear complementarity problem (SDLCP) and established polynomial convergence of a feasible short-step pathfollowing algorithm based on a particular direction of their family. The question of whether polynomiality could be established for any direction of their family thus remained an open problem. This paper a...

In this paper a symmetric primal-dual transformation for positive semideenite programming is proposed. For standard SDP problems, after this symmetric transformation the primal variables and the dual slacks become identical. In the context of linear programming, existence of such a primal-dual transformation is a well known fact. Based on this symmetric primal-dual transformation we derive Newt...

Consider linear programs in dual standard form with n constraints and m variables. When typical interior-point algorithms are used for the solution of such problems, updating the iterates, using direct methods for solving the linear systems and assuming a dense constraint matrix A, requires O(nm) operations per iteration. When n ≫ m it is often the case that at each iteration most of the constr...

The main ideas of path following by predictor-corrector and piecewise-linear methods, and their application in the direction of homotopy methods and non-linear eigenvalue problems are reviewed. Further new applications to areas such as polynomial systems of equations, linear eigenvalue problems, interior methods for linear programming, parametric programming and complex bifurcation are surveyed...

This paper deals with the state estimation problem for linear systems with state equality constraints. Using noisy measurements which are available from the observable system, we construct the optimal estimate which also satisfies linear equality constraints. For this purpose, after reviewing modeling problems in linear stochastic systems with state equality constraints, we formulate a projecte...

This paper is concerned with sensor data transmission strategy. The main focus of the paper is how to reduce the number of sensor data transmission while maintaining the difference between the estimated sensor value and the real sensor value. The proposed method could be used in sensor networks and networked control systems, where number of transmission should be minimal. A linear predictor is ...

A rigorous analysis of the blind source extraction (BSE) approach based on a linear predictor is provided. It is shown that by minimising the mean squared prediction error (MSPE), as originally proposed, it is only possible to reach a solution subject to an arbitrary orthogonal transformation. To remove this ambiguity, a new cost function based on the normalised MSPE is introduced which by desi...

In prediction problems with more predictors than observations, it can sometimes be helpful to use a joint probability model, π(Y,X), rather than a purely conditional model, π(Y | X), where Y is a scalar response variable and X is a vector of predictors. This approach is motivated by the fact that in many situations the marginal predictor distribution π(X) can provide useful information about th...