Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in the ...
Milpitas, Calif.— A singular value decomposition (SVD) core generator has been added to AccelChip Inc.'s AccelWare advanced math tool kit. Aimed at sensor array processing, the SVD core generator ...
MILPITAS, CA, June 1, 2005 – Building upon its recent releases of matrix inversion and factorization parameterized cores, AccelChip Inc., the industry’s only provider of automated flows from ...
Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...
Radar, navigation and guidance systems process data that is acquired using arrays of sensors. The energy delta from sensor to sensor over time holds the key to information such as targets, position or ...
A new study evaluates three distinct algorithms—Band Shape Fitting (BSF), Three-band Fraunhofer Line Discrimination (3FLD), and Singular Vector Decomposition (SVD)—to retrieve far-red solar-induced ...