Adaptive Dithering Of One Dimensional Signals

This work presents a novel dithering algorithm for one dimensional signals. Standard dithering with a triangular probability density white noise increases the noise level by 6dB. This technique is numerically based instead of statistically based, and the increase in noise level can be specified as low as 3dB. The problem is reduced to a set of non-linear simultaneous equations that are solved using any number of optimization techniques. In this paper, a solution using Levenberg-Marquardt is shown and is compared to standard dithering with both real and synthetic signals.