In this paper, the authors describe the concept of adaptive noise cancelling, an alternative method of estimating signals corrupted by additive noise or interference. A desired signal corrupted by additive noise can often be recovered by an adaptive noise canceller using the Least Mean Squares (LMS) algorithm. This adaptive noise canceller is then useful for enhancing the S/N ratio of data collected from sensors (or sensor arrays) working in noisy environment, or dealing with potentially weak signals. The principle advantages of the method are its adaptive capability, its low output noise, and its low signal distortion.