Jacobi method and Gauss-Seidel method ,

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SUMMARY

The discussion focuses on the convergence of the Jacobi method and the Gauss-Seidel method for solving linear systems. The user proposes to demonstrate convergence by showing that the spectral radii, ρ(Tj) and ρ(Tg), are both less than 1, where ρ(A) represents the spectral radius of matrix A. The user also seeks faster methods for solving linear systems beyond these iterative techniques. Key equations include ρ(Tj) = D-1(L + U) and ρ(Tg) = (D + L)-1U, with A defined as A = D - L - U.

PREREQUISITES
  • Understanding of iterative methods for solving linear systems
  • Familiarity with matrix theory, specifically spectral radius
  • Knowledge of the Jacobi method and Gauss-Seidel method
  • Basic linear algebra concepts, including diagonal, lower-triangular, and upper-triangular matrices
NEXT STEPS
  • Research the convergence criteria for iterative methods in numerical analysis
  • Explore advanced iterative methods such as Successive Over-Relaxation (SOR)
  • Learn about the implications of spectral radius on convergence speed
  • Investigate the application of matrix norms in analyzing convergence
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Students and professionals in mathematics, engineering, and computer science who are studying numerical methods for solving linear equations, particularly those interested in the efficiency and convergence of iterative methods.

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Homework Statement



for part c , it asked for showing both 2 method converge for any initial condition.
I think we can show that by using $$ρ(T_{j}), ρ(T_{g}) <1 $$
I want to know whether it's correct or not , and is there any faster method?

Homework Equations


$$ρ(A)$$ means spectral radius of matrix A.
And $$ρ(T_{j})=D^{-1}(L+U) , ρ(T_{g})=(D+L)^{-1}U $$
where$$ A=D-L-U$$ , D is the diagonal matrix -L is strictly lower-triangular part of A,
-U is strictly upper-triangular part of A.

The Attempt at a Solution

 

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