Extraction of multiple periodic waveforms from noisy data

This paper presents a novel approach to the extraction of weaker periodic signals in the presence of noise and a stronger periodic waveform. The signals may have any shape, not necessarily sinusoidal in nature. The approach is based on the Singular Value Decomposition. The extraction procedure consists of two steps, identifying the strongest periodic component and consequent configuring the data matrix followed by extraction of this component. This process is repeated till all the components have been recovered. The approach is both simple and robust and requires no additional reference inputs. The simplicity of the scheme is however, at the expense of certain inherent limitations, which are also investigated