What does "Subspace Methods" mean?

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Subspace methods are techniques used in various fields, such as computer science and engineering, to make complex problems simpler and easier to solve. They work by focusing on a smaller part of the data or problem rather than dealing with everything at once.

When faced with large amounts of information or complicated calculations, subspace methods help by breaking down the task. Instead of looking at every detail, these methods look at key aspects that capture the most important features. This approach can save time and effort, making it more manageable to reach solutions.

In practical applications, such as fluid simulations or sound direction estimation, subspace methods allow for effective analysis without getting overwhelmed by the entire dataset. They help improve performance and accuracy while keeping the process efficient.

Overall, subspace methods provide a way to handle complex systems by focusing on the most relevant parts, making it easier to achieve results in various scientific and engineering tasks.