Math Problem Statement
[0.46153846 1.96153846 2.46153846 1.96153846 0.46153846] 我得到了这样的一个解 如何根据图片上面说的惨差值 来校验数据?
Solution
To verify the data using the discrepancy value () as described in the text, follow these steps:
1. Understanding the concept
The text explains that a well-posed system () is sensitive to small perturbations in the right-hand side vector () and/or the coefficients () of the matrix . A system is considered poorly conditioned if these perturbations cause large errors in the solution ().
The sensitivity is quantified using the condition number of the matrix , denoted as . A high condition number indicates a poorly conditioned system.
2. Steps to calculate and verify the solution
To validate your solution:
-
Condition number:
- Compute . This tells you how sensitive the system is to errors.
- If is very large, the system may be unstable.
-
Compute residual ():
- Use the formula , where is the coefficient matrix, is your solution vector, and is the right-hand side vector.
- A small residual (close to 0) indicates the solution is consistent with the system.
-
Relative error:
- Estimate the relative error in the solution due to perturbations () using:
- Here, represents any small changes or errors in .
-
Validation:
- Compare the calculated relative error and condition number to thresholds that indicate whether the system is well-posed.
3. Applying this to your solution
If the solution vector is: and you have the system , you need:
- Matrix
- Right-hand side vector
Example:
- If and are known, calculate .
- Compute the condition number .
- Verify that small changes in (e.g., ) result in proportional changes in according to the formula above.
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Math Problem Analysis
Mathematical Concepts
Linear Algebra
Condition Number
Residuals in Systems of Linear Equations
Formulas
Residual: r = Ax - b
Relative Error: (||Δx*|| / ||x||) ≈ cond(A) * (||Δb|| / ||b||)
Condition Number: cond(A) = ||A|| * ||A^-1||
Theorems
Sensitivity Analysis in Linear Systems
Suitable Grade Level
Undergraduate Level
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