Through many examples and real-world applications, this text teaches undergraduate-level linear algebra in a comprehensive, geometric, and algorithmic way. It provides a solid foundation for further work in math, engineering, science, computer graphics, and geometric modeling. Along with more exercises and applications, this third edition covers singular value decomposition and its application to the pseudoinverse, principal components analysis, and image compression. It also gives more attention to eigen-analysis, ...
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Through many examples and real-world applications, this text teaches undergraduate-level linear algebra in a comprehensive, geometric, and algorithmic way. It provides a solid foundation for further work in math, engineering, science, computer graphics, and geometric modeling. Along with more exercises and applications, this third edition covers singular value decomposition and its application to the pseudoinverse, principal components analysis, and image compression. It also gives more attention to eigen-analysis, including eigenfunctions and the Google matrix, and emphasizes orthogonal projections and matrix decompositions.
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