noiseinsensitive
Noiseinsensitive refers to the property of a system, estimator, or algorithm to produce outputs that are relatively unaffected by random noise or disturbances in the input or environment. The concept is used across engineering, statistics, machine learning, and signal processing to distinguish methods that withstand measurement error or environmental fluctuations from those that are highly sensitive to noise.
In signal processing and statistics, noise-insensitive approaches include robust estimators such as median filters for impulse
Techniques commonly associated with noise-insensitive performance include robust statistics, redundancy and voting schemes, denoising through wavelet
Applications span telecommunications, image and audio processing, sensor networks, robotics, and finance, where reliable performance under