Savitzky-Kolmogorov Theorem

The Savitzky-Golay theorem relates to a method used to smooth or filter data, especially when analyzing signals or measurements. It involves fitting small segments of data to a polynomial curve using least squares and then using this fitted curve to smooth out noise or fluctuations while preserving the underlying pattern. Essentially, it helps improve the clarity of data without distorting important features, making it valuable in fields like spectroscopy, chemistry, and signal processing for extracting meaningful information from noisy data sets.