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Theoretical and computational studies of the least square method and its variations

Grant number: 21/04506-2
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): July 01, 2021
Effective date (End): June 30, 2022
Field of knowledge:Physical Sciences and Mathematics - Mathematics - Applied Mathematics
Principal researcher:Cassio Machiaveli Oishi
Grantee:Daniel Henrique Serezane Pereira
Home Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
Associated research grant:13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID


In this project we will investigate the least squares method for approximating discrete data. Initially, classic Linear Algebra topics will be analyzed, such as orthogonalization, matrix decompositions, eigenvalues and eigenvectors, etc. After this stage, the student will implement the most known techniques for computationally solving the least squares methods for data approximation. Lastly, special attention will be given to the method's applications and variations involving artificial intelligence.