 Generalized singular value decomposition

Generalized Singular Value Decomposition (GSVD) is an extension of the standard singular value decomposition (SVD) that applies to pairs (or sets) of matrices. It is a mathematical technique used in linear algebra and statistics primarily for solving problems involving two matrices, particularly in the context of solving systems of linear equations, dimensionality reduction, and multivariate data analysis.