In this paper, a method for optimizing the number and the configuration of control sources in an active control system is proposed. In the optimization process, sources are selected one by one so that the corresponding transfer impedance vector is the most linearly independent. From the results of the simulation, it is shown that the optimized configuration yields not only small average control...

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...

In this paper, a new algorithm using 2DPCA and Gram-Schmidt Orthogonalization Procedure for recognition of face images is proposed. The algorithm consists of two parts. In the first part, a common feature matrix is obtained; and in the second part, the dimension of the common feature matrix is reduced. Resulting common feature matrix with reduced dimension is used for face recognition. Column a...

Over the last years, numerous equalization schemes for multiple-input/multiple-output (MIMO) channels have been studied in literature. In particular, techniques known from intersymbol-interference channels have been transferred to the MIMO setting, such as linear equalization, decision-feedback equalization (DFE, also known as successive interference cancellation, SIC, and the main ingredient o...

Mechanical properties in crystals are determined by the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a new tool to image and interpret dislocations within using multidimensional scans. However, methods required reconstruct meaningful dislocation information from high-dimensional DFXM scans still nascent require significant manu...

We consider the Modified Gram-Schmidt orthogonalization applied to a matrix A ∈ Rm×n. This corresponds to a QR factorization : A = QR. We study this algorithm in finite precision computation when the matrix A has a numerical rank deficiency k. This subject has already been dealt with success by Björck and Paige in 1992 [1]. They give useful bounds in term of norms. We extend their results to pr...

The deep active-subspace method is a neural-network based tool for the propagation of uncertainty through computational models with high-dimensional input spaces. Unlike original method, it does not require access to gradient model. It relies on an orthogonal projection matrix constructed Gram–Schmidt orthogonalization reduce dimensionality. This incorporated into neural network as weight first...

Our problem is to accurately solve linear systems on a general purpose graphics processing unit with double double and quad double arithmetic. The linear systems originate from the application of Newton’s method on polynomial systems. Newton’s method is applied as a corrector in a path following method, so the linear systems are solved in sequence and not simultaneously. One solution path may r...

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We propose an alternative orthonormalization method that computes the orthonor-mal basis from the right singular vectors of a matrix. Its advantage are: a) all operations are matrix-matrix multiplications and thus cache-eecient, b) only one synchronization point is required in parallel implementations, c) could be more stable than Gram-Schmidt. In addition, we consider the problem of incrementa...