The paper is concerned with simultaneous linear-quadratic (LQ) optimal control design for a set of LTI systems via piecewise constant output feedback. First, the discrete-time simultaneous LQ optimal control design problem is reduced to solving a set of coupled matrix inequalities and an iterative LMI algorithm is presented to compute the feedback gain. Then, simultaneous stabilization and simu...

We propose a novel algorithm to register multiple 3D point sets within a common reference frame simultaneously. Our approach performs an explicit optimisation on the manifold of rotations. Firstly, we present a new closed-form solution for simultaneous multiview registration in the noise-free case. Secondly, we use this as a first step to derive a good initial estimate of a solution in the case...

This paper proposes a scan-matching simultaneous localisation and mapping (SLAM)-based Iterative Closest Point algorithm using laser scan information and images in an indoor environment. The ICP algorithm, which is one of the scan-matching methods calculates the closest position iteratively by adjusting the motion vector and rotation matrix of the model. The matching process requires a great de...

When an autonomous mobile robot acts in constructed environments, a map that has the information about obstacles is necessary for the mobile robot. Even if a map is given, however, the mobile robot cannot start its action without the information of its present location on the map. Therefore, techniques of map generation and self-localization are important for mobile robots. In this paper, we pr...

The authors define ordered subset processing for standard algorithms (such as expectation maximization, EM) for image restoration from projections. Ordered subsets methods group projection data into an ordered sequence of subsets (or blocks). An iteration of ordered subsets EM is defined as a single pass through all the subsets, in each subset using the current estimate to initialize applicatio...

We present a technique for the iterative diagonalization of random-phase approximation (RPA) matrices, which are encountered in the framework of time-dependent density-functional theory (TDDFT) and the Bethe-Salpeter equation. The non-Hermitian character of these matrices does not permit a straightforward application of standard iterative techniques used, i.e., for the diagonalization of ground...

The paper proposes a segmentation procedure inspired to a robust LIDaR filtering data method recently introduced by the authors. The method is based on the application of a Simultaneous AutoRegressive (SAR) model for describing a trend surface and of an iterative Forward Search (FS) algorithm to detect clusters of non-stationary data. The procedure consists in an automatic process to identify r...

Real-time learning requires on-line complexity estimation. Expectation-maximisation (EM) and sampling techniques are presented that enable simultaneous estimation of the complexity and continuous parameters of Gaussian mixture models (GMMs) which can be used for density estimation, classiication and feature extraction. The solution is a maximum a posteriori probability (MAP) estimator that is c...

We propose a novel multiscale algorithm for the problem of model assimilation of data. The algorithm allows one to efficiently perform optimal statistical interpolation of observed data from a given forecast wf and vector of observations wo. The core of the new approach is a combination of two multiscale tools: a multiresolution iterative process and a multigrid fastsummation technique. Our app...

Real-time learning requires on-line complexity estimation. Expectation-maximisation (EM) and sampling techniques are presented that enable simultaneous estimation of the complexity and continuous parameters of Gaussian mixture models (GMMs) which can be used for density estimation, classi cation and feature extraction. The solution is a maximum a posteriori probability (MAP) estimator that is c...