What are the advantages of the Gauss-Seidel method?
The Gauss-Seidel method is advantageous because it converges faster than the Jacobi method and is easy to implement.
Can you explain why it converges faster?
It converges faster due to its use of updated values immediately, which allows for quicker adjustments in each iteration.
Are there any limitations to using Gauss-Seidel?
Yes, it may not converge for all types of matrices, especially if they are not diagonally dominant.
How does it compare to other methods like SOR?
Compared to Successive Over-Relaxation (SOR), Gauss-Seidel is simpler but SOR can be faster with the right relaxation factor.
In what scenarios is Gauss-Seidel preferred?
It's preferred for solving large, sparse systems of linear equations where speed and simplicity are crucial.
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