Enhanced gram-schmidt process for improving the stability in signal and image processing

By: Contributor(s): Material type: ArticleArticleDescription: 1 archivo (131,1 KB)Subject(s): Online resources: Summary: The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors) into an orthonormal basis (a set of orthogonal, unit-length vectors). The process consists of taking each vector and then subtracting the elements in common with the previous vectors. This paper introduces an Enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for signal and image processing applications.
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Capítulo de libro Capítulo de libro Biblioteca de la Facultad de Informática Biblioteca digital A0438 (Browse shelf(Opens below)) Link to resource Recurso en Línea

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The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors) into an orthonormal basis (a set of orthogonal, unit-length vectors). The process consists of taking each vector and then subtracting the elements in common with the previous vectors. This paper introduces an Enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for signal and image processing applications.

International Journal of Mathematical, Computational, Physical and Quantum Engineering, 7(3), pp. 342-346