Least Mean Squares (LMS)

The Least Mean Squares (LMS) algorithm is a method used in signal processing and adaptive systems to continuously improve predictions or filters. It works by making an initial guess, then measuring how far off that guess is from the actual result. The algorithm adjusts its parameters incrementally to reduce the error, essentially "learning" from mistakes. Over time, these adjustments help the system better predict or filter signals, such as removing noise from audio or improving communication signals. LMS is valued for being simple, computationally efficient, and effective in real-time applications where conditions change dynamically.