Question:

Let \( A \) be a \( 3 \times 3 \) real matrix and \( b \) be a \( 3 \times 1 \) real column vector. Consider the statements:
1. The Jacobi iteration method for the system \( (A + \epsilon I_3)x = b \) converges for any initial approximation and \( \epsilon>0 \).
2. The Gauss-Seidel iteration method for the system \( (A + \epsilon I_3)x = b \) converges for any initial approximation and \( \epsilon>0 \).
Which one of the following is correct?

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For iterative methods, check conditions like diagonal dominance or positive definiteness to ensure convergence.
Updated On: Feb 1, 2025
  • Both I and II are TRUE
  • I is TRUE and II is FALSE
  • I is FALSE and II is TRUE
  • Both I and II are FALSE
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The Correct Option is A

Solution and Explanation

Step 1: Understanding the iteration methods. The Jacobi and Gauss-Seidel methods for solving \( Ax = b \) converge if \( A \) is strictly diagonally dominant or positive definite. Adding \( \epsilon I_3 \) ensures that \( A + \epsilon I_3 \) becomes strictly diagonally dominant for \( \epsilon>0 \). Step 2: Verifying convergence conditions. - For Jacobi method: \( (A + \epsilon I_3) \) is strictly diagonally dominant, ensuring convergence. - For Gauss-Seidel method: \( (A + \epsilon I_3) \) being strictly diagonally dominant also ensures convergence. Step 3: Conclusion. Both statements are true. The correct answer is \( {(1)} \).
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