In this paper, we propose algorithms which preserve energy in empirical mode decomposition (EMD), generating finite n number of band limited Intrinsic Mode Functions (IMFs). In the first energy preserving EMD (EPEMD) algorithm, a signal is decomposed into linearly independent (LI), non orthogonal yet energy preserving (LINOEP) IMFs and residue (EPIMFs). It is shown that a vector in an inner pro...

Selected Common Threads and Root Concepts Linking Old to New Sandra L. Arlinghaus* and Joseph Kerski** Introduction In the twentieth century, much of mathematics experienced a well-known paradigm shift in moving from a focus on mathematical objects to a focus on transformations of objects. Thus, one sees, for example, linear algebra courses that focus on matrix vector products as linear transfo...

This paper presents a branch-and-lift algorithm for solving optimal control problems with smooth nonlinear dynamics and potentially nonconvex objective and constraint functionals to guaranteed global optimality. This algorithm features a direct sequential method and builds upon a generic, spatial branch-and-bound algorithm. A new operation, called lifting, is introduced, which refines the contr...

By the example of a mathematical model of a biochemical process, the structural instability of dynamical systems is studied by calculating the full spectrum of Lyapunov indices with the use of the generalized Benettin algorithm. For the reliability of the results obtained, the higher Lyapunov index determined with the orthogonalization of perturbation vectors by the Gram– Schmidt method is comp...

A procedure for sampling lattice vectors is at the heart of many lattice constructions, and the algorithm of Klein (SODA 2000) and Gentry, Peikert, Vaikuntanathan (STOC 2008) is currently the one that produces the shortest vectors. But due to the fact that its most time-efficient (quadratic-time) variant requires the storage of the GramSchmidt basis, the asymptotic space requirements of this al...

Many blind adaptive beamforming algorithms require the selection of one or more non-zero initial weight vectors. Proper selection of the initial weight vectors can speed algorithm convergence and help ensure convergence to the desired solutions. Three alternative initialization approaches are compared here, all of which depend only on second order statistics of the observed data. These methods ...

This paper deals with an application of regression analysis to the regulation of the blood-sugar under diabetes mellitus. Section 2 gives a description of Gram-Schmidt orthogonalization, while Section 3 discusses the difference between Gauss-Markov estimation and Least Squares Estimation. Section 4 is devoted to the statistical analysis of the blood-sugar during the night. The response change o...

In this paper, we propose novel blind separation techniques for multiple-input multiple-output systems based on least-squares constant modulus algorithm (LSCMA). To ensure that each output signal is extracted from different input signals, the proposed algorithms have been derived by using successive interference cancellation and Gram-Schmidt orthogonalization procedure. The performance is obser...