[EN] The input and output signals of a digital signal processing system can often be represented by a rectangular matrix as it is the case of the beamformer algorithm, a very useful particular algorithm that allows extraction of the original input signal once it is cleaned from noise and room reverberation. We use a version of this algorithm in which the system matrix must be factorized to solve a least squares problem. The matrix changes periodically according to the input signal sampled; therefore, the factorization needs to be recalculated as fast as possible. In this paper, we propose to use parallelism through a pipeline pattern. With our pipeline, some partial computations are advanced so that the final time required to update the fac...
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
Many scientific or engineering applications involve matrix operations, in which reduction of vectors...
This thesis presents four contributions: first, it develops new techniques to extend the range of ap...
There exist problems in the field of digital signal processing, such as filtering of acoustic signal...
The processing of digital sound signals often requires the computation of the QR factorization of a ...
AbstractLinear least squares problems are commonly solved by QR factorization. When multiple solutio...
n this paper we propose new stable parallel algorithms based on Householder transformations and comp...
Matrix decomposition and computation constitute an important part of various signal processing, imag...
The least squares problem is an extremely useful device to represent an approximate solution to over...
The QR factorization is one of the most important operations in dense linear algebra, offering a num...
Linear least squares problems are commonly solved by QR factorization. When multiple solutions have ...
The least squares problem is an extremely useful device to represent an approximate solution to over...
QR decomposition is a key operation in many current communication systems. This paper shows how to ...
In this paper we study how to update the solution of the linear system Ax = b after the matrix A is ...
Computationally efficient parallel algorithms for downdating the least squares estimator of the ordi...
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
Many scientific or engineering applications involve matrix operations, in which reduction of vectors...
This thesis presents four contributions: first, it develops new techniques to extend the range of ap...
There exist problems in the field of digital signal processing, such as filtering of acoustic signal...
The processing of digital sound signals often requires the computation of the QR factorization of a ...
AbstractLinear least squares problems are commonly solved by QR factorization. When multiple solutio...
n this paper we propose new stable parallel algorithms based on Householder transformations and comp...
Matrix decomposition and computation constitute an important part of various signal processing, imag...
The least squares problem is an extremely useful device to represent an approximate solution to over...
The QR factorization is one of the most important operations in dense linear algebra, offering a num...
Linear least squares problems are commonly solved by QR factorization. When multiple solutions have ...
The least squares problem is an extremely useful device to represent an approximate solution to over...
QR decomposition is a key operation in many current communication systems. This paper shows how to ...
In this paper we study how to update the solution of the linear system Ax = b after the matrix A is ...
Computationally efficient parallel algorithms for downdating the least squares estimator of the ordi...
The increasing complexity of modern computer architectures has greatly influenced algorithm design. ...
Many scientific or engineering applications involve matrix operations, in which reduction of vectors...
This thesis presents four contributions: first, it develops new techniques to extend the range of ap...