We show the application of a denoising implementation for visualizing single-trial evoked potentials. Its performance is shown in simulated data as well as in human evoked potentials. For the simulated data, the method gives a significantly better reconstruction of the single-trial responses in comparison with the original data and also in comparison with a reconstruction based on conventional Wiener filtering. For the real data, the method clearly improves the visualization of the single-trial responses. This allows the study of the variability between trials, which can be linked to processes such as habituation, sensitization, learning, atention, etc. Since the method is fast and parameter free, it could complement the conventional analysis of event-related potentials.