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 6 dB. This technique is numerically based instead of statistically based, and the increase in noise level can be specified as low as 3 dB. 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.