Search results for "Gaussian elimination"
showing 4 items of 4 documents
Hardware-efficient matrix inversion algorithm for complex adaptive systems
2012
This work shows an FPGA implementation for the matrix inversion algebra operation. Usually, large matrix dimension is required for real-time signal processing applications, especially in case of complex adaptive systems. A hardware efficient matrix inversion procedure is described using QR decomposition of the original matrix and modified Gram-Schmidt method. This works attempts a direct VHDL description using few predefined packages and fixed point arithmetic for better optimization. New proposals for intermediate calculations are described, leading to efficient logic occupation together with better performance and accuracy in the vector space algebra. Results show that, for a relatively s…
What is the Best Method of Matrix Adjustment? A Formal Answer by a Return to the World of Vectors
2003
The principle of matrix adjustment methods consists into finding what is the matrix which is the closest to an initial matrix but with respect of the column and row sum totals of a second matrix. In order to help deciding which matrix-adjustment method is the better, the article returns to the simpler problem of vector adjustment then back to matrices. The information-lost minimization (biproportional methods and RAS) leads to a multiplicative form and generalize the linear model. On the other hand, the distance minimization which leads to an additive form tends to distort the data by giving a result asymptotically independent to the initial matrix. The result allows concluding non-ambiguou…
Systems of Linear Equations
2016
A linear equation in \(\mathbb {R}\) in the variables \(x_1,x_2,\ldots ,x_n\) is an equation of the kind:
Cluster Algorithm Integrated with Modification of Gaussian Elimination to Solve a System of Linear Equations
2020
The data accumulation and their inhomogeneous distribution lead to the issue of large and sparse systems solving in various fields: industrials, emergency management, etc. Complex structure in the data error creates additional risk to obtain an adequate solution. To facilitate problem-solving, we describe the technique that is based on intellectual division of data with following application of cluster algorithm and the modification of Gaussian elimination to different portions of data. In this paper, we present results of developed technique that was applied to samples of synthetic and real data. We compare them with outcomes of other algorithms (intelligence and classical) by using of num…