Bispectral reconstruction using incomplete phase knowledge: a neuroelectric signal estimation application

The bispectral averaging technique is often used in order to analyze signal with variable signal delay, in presence of noise. Unfortunately, as the bispectrum is time-shift invariant, the initial phase of the signal can´t be recovered. When studying somatosensory evoked potentials (neuroelectric signals) this phase is generally the major information, especially when it characterizes pathologies. We show that some information about this phase can be extracted from the averaged signal. An attempt to include this knowledge in the magnitude and phase recovery algorithms is made. We illustrate the benefits of this approach on a simulation and a real application leading to a details enhancement of the analyzed signal