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Lecture
Conjugate Gradient Method: Solving Linear Systems
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Related lectures (30)
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Effect of Rounding Errors in Linear Systems
Explores the effect of rounding errors in solving linear systems using the LU factorization method.
Iterative Methods for Linear Equations
Explores iterative methods for linear equations, including Jacobi and Gauss-Seidel methods, convergence criteria, and the conjugate gradient method.
Linear Systems: Direct and Iterative Methods
Explores linear systems, covering direct and iterative methods for solving them with a focus on round-off errors and Richardson's algorithm.
Construction of an Iterative Method
Covers the construction of an iterative method for linear systems, emphasizing matrix decomposition and convexity.
The Conjugate Gradients Method (CG)
Covers the Conjugate Gradients method for solving linear systems iteratively with quadratic convergence and emphasizes the importance of linear independence among conjugate directions.
Regression & Systemed Lineaires
Covers the principles of regression and linear systems, focusing on iterative methods.
Iterative Solvers: Theory and Comparison
Explores solving linear systems iteratively and compares different solvers based on worst-case assumptions and convergence measures.
Eigenvalue Problems: Methods and Applications
Explores eigenvalue problems, iterative methods, and their applications in quantum physics and network analysis.
Construction of an Iterative Method
Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.
Linear Systems: Diagonal and Triangular Matrices, LU Factorization
Covers linear systems, diagonal and triangular matrices, and LU factorization.
