Tikhonov regularization

Tikhonov regularization is a way to solve a mathematical problem where we want to find the best answer to a question but we don't have enough information.

Imagine you have a puzzle with missing pieces. You want to complete the puzzle, but some of the pieces are missing, so you don't know what the final picture should look like. To solve this problem, you try to find a picture that is similar to the original one, based on the information that you do have.

Tikhonov regularization works the same way. It tries to find a solution to a problem, even when we don't have all the information we need. It finds an answer that is as close as possible to the correct one, while also making sure that the answer is not too complex.

This method is used in many areas of science and engineering, such as data analysis, image processing, and even medicine. By using Tikhonov regularization, scientists and engineers can find the best possible answer to a problem, even when the problem is incomplete or uncertain.