Lecture
Linear Systems Resolution
Related lectures (42)
Iterative Methods: Linear Systems
Covers iterative methods for solving linear systems and discusses convergence criteria and spectral radius.
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Explores linear systems, Gaussian elimination, LU decomposition, and matrix types.
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Introduces iterative methods for solving linear equations and discusses the gradient method for minimizing errors.
Gauss-Seidel Method
Covers the Gauss-Seidel method for solving linear systems with triangular matrices and progressive substitution.
Richardson Convergence
Explains convergence criteria and optimal choices for Richardson iteration method, including error estimation and matrix conditioning.
Direct and Iterative Methods for Linear Equations
Explores direct and iterative methods for solving linear equations, emphasizing symmetric matrices and computational cost.
Gaussian Elimination: BasicsMOOC: Numerical Analysis for Engineers
Covers the basics of Gaussian elimination and the iterative steps involved in the process.
Linear Systems: Iterative Methods
Explores linear systems and iterative methods like gradient descent and conjugate gradient for efficient solutions.
Conjugate Gradient Method
Covers the Conjugate Gradient method for solving linear systems efficiently.
Direct Methods for Linear Equations
Covers direct methods for solving linear equations and computation complexity of substitution.