|
Numerical methods: tasks solving on the computer.
Programming in Matlab.
Programming in Matlab.
Programming in Matlab.
The problem and source of numerical errors. Basic criteria in numerical analysis (conditioning) and numerical algorithms (error, complexity, stability, correctness).
Monte Carlo methods. Recursion.
Vector and matrix norms and their properties, condition number, Gershgorin theorem.
Direct methods of solving systems of linear equations.
Iterative methods of solving large systems of linear equations. Sparse matrices.
Jacobi, Gauss-Seidel, Richardson methods. Their convergence and implementation.
Systems of nonlinear equations. Banach method.
Newton's method.
Newton's method.
Applications of numerical algorithms in various areas of science.
Applications of numerical algorithms in artificial intelligence.
|
