Inverse Problems
Numerical stability refers to the property of an algorithm to produce small changes in output in response to small changes in input. In the context of solving inverse problems, ensuring numerical stability is crucial as it affects the accuracy and reliability of the computed solutions, especially when dealing with ill-posed problems or noise in the data. Different iterative methods, matrix factorizations, and algorithms can exhibit varying levels of numerical stability, which influences their effectiveness in practical applications.
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