the matrix functions appear in several applications in engineering and sciences. the computation of these functions almost involved complicated theory. thus, improving the concept theoretically seems unavoidable to obtain some new relations and algorithms for evaluating these functions. the aim of this paper is proposing some new reciprocal for the function of block anti diagonal matrices. more...

Matrix multiplication is a computationally-intensive and fundamental matrix operation in many algorithms used in scientific computations. It serves as the basic building block for signal, image processing, graphics and robotic applications. To improve the performance of these applications, a high performance matrix multiplier is required. Traditionally, matrix multiplication operation is either...

— In this paper, an algorithm for construction of multiple sets of two dimensional (2D) or matrix unipolar (optical) orthogonal codes has been proposed. Representations of these 2D codes in difference of positions representation (DoPR) have also been discussed along-with conventional weighted positions representation (WPR) of the code. This paper also proposes less complex methods for calculati...

We implement a flexible Z-matrix approach in the Density Functional Theory (DFT) periodic boundary conditions code, SIESTA. This allows a mixture of Z-matrix and Cartesian coordinates to be used for geometry specification and optimisation. In addition, geometry constraints in the form of fixed coordinates and fixed linear relationships between coordinates can be specified. A Z-matrix approach i...

Three-dimensional electron microscopy (3D-EM) is a powerful technology for imaging macromolecular complexes. Through a process known as singleparticle reconstruction, tens of thousands of separate images of a complex of interest are used to arrive at a single resolved structure. Although this method works sufficiently well for rigid macromolecular complexes, conformationally flexible complexes ...

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible ...