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Definitions from the WebSVD (Singular Value Decomposition)Definition: SVD, also known as Singular Value Decomposition, is a key mathematical technique used in linear algebra and numerical analysis. It decomposes a matrix into singular values and corresponding singular vectors. Sense 1 (Noun): In mathematics, SVD refers to the factorization of a matrix where the matrix M is represented as the product of three separate matrices: U, Σ, and V. Here, U and V are unitary matrices, while Σ is a diagonal matrix. SVD is widely used for analyzing data, data compression, and solving linear systems of equations. Example sentence: The SVD algorithm provides an efficient way to reduce the dimensionality of large datasets while preserving the most important information. Sense 2 (Noun): In medical terminology, SVD stands for Spontaneous Vaginal Delivery, a type of childbirth where the baby is born through the birth canal without the need for medical interventions or surgical procedures. Example sentence: The doctor recommended a SVD as the preferred method of delivery, considering the mother's health condition and the baby's position. Sense 3 (Noun): In computer science, SVD may refer to Sparse Vector Decomposition, a method that decomposes a sparse vector into a set of basis vectors and corresponding coefficients. Example sentence: The SVD technique can effectively represent sparse vectors in a compact form, making them easier to process and analyze. Related products on Amazon: | ||||
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