Hint for a problem on condition number

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In summary, the conversation discusses the problem of computing the condition number of a linear system and whether the system is well-conditioned with respect to perturbations of the right-hand side constants. The condition number is found to be 1601 and was computed using the norm of the matrix A and its inverse. The conversation also touches on the formula for finding the norm and the type of vector norm used. It is determined that this information is sufficient for the purpose of the problem.
  • #1
kalish1
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I would like to know if the second part of this question is asking something different.

**Problem:** Consider the linear system $19x_1+20x_2=b_1, 20x_1+21x_2=b_2$. Compute the condition number of the coefficient matrix. Is the system well-conditioned with respect to perturbations of the right-handside constants ${b_1,b_2}$?

Do I need to introduce a $\delta$ into the right-handside, or is computing the coefficient number enough to conjecture about the condition of the right-handside constants?

Thanks.
 
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  • #2
The second part of the problem as asking if the condition number you just computed is highly dependent on $b_{1}$ and $b_{2}$. What happens if you change the RHS's just a little? Does the condition number change a lot when you do that? I don't think you need to introduce another variable, at least not yet. What do you get for the condition number? And how are you computing it?
 
  • #3
I get 1601 = 41*41 for the condition number, and I got it by computing the norm of the matrix A and the norm of the matrix A^(-1), an then multiplying them together. The norms of the matrices are both 41.

Isn't this enough for the purposes of this problem?
 
  • #4
Did you use the formula
$$\|A\|= \max \{ \|Ax \|:x \in \mathbb{R}^{2}, \|x \|=1 \}?$$
If so, what vector norm did you use? Euclidean?
 
  • #5
I used the following norm:

$$\|A_{n\mathbb x n}|=\max_{1\leq i \leq n}\sum_{j=1}^{n}\|a_{ij}\|$$
 

FAQ: Hint for a problem on condition number

What is a condition number?

A condition number is a measure of how sensitive a mathematical problem is to changes in its inputs. In other words, it measures how much the output of a problem will change if there is a small change in the input values.

How is the condition number calculated?

The condition number is calculated by taking the ratio of the maximum change in the output to the maximum change in the input. It is typically represented by the symbol κ (kappa) and is a non-negative value.

Why is the condition number important?

The condition number is important because it gives insight into the reliability and accuracy of a solution to a problem. A high condition number indicates that the problem is ill-conditioned and could result in errors or instability in the solution.

How does the condition number affect numerical algorithms?

The condition number can greatly impact the performance of numerical algorithms. A high condition number can result in slower convergence, loss of numerical stability, and inaccuracies in the solution. It is important to consider the condition number when selecting an appropriate numerical algorithm for a problem.

How can we improve the condition number of a problem?

The condition number of a problem can be improved by using a different formulation or approach to the problem, choosing a different set of input values, or using more precise numerical methods. It is also important to avoid dividing by small numbers or taking the difference between two nearly equal numbers, as this can greatly increase the condition number.

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