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Numerical by cs25b1028 is a document available to read on EtoBox.

What is Numerical about?

The document analyzes the challenges of computing derivatives from noisy data, highlighting that differentiation amplifies noise and can lead to ill-posed problems. It outlines a methodology involving representation, truncation, differentiation, and error analysis, testing various noise levels. The findings indicate that the method is accurate for low noise (up to 20%) but degrades significantly at higher noise levels (30%+), with stability depending on the choice of cut-off N.

Author
cs25b1028
Language
EN