  The zeros of the spectrogram have proven to be a relevant feature to describe
the time-frequency structure of a signal, originated by the destructive
interference between components in the time-frequency plane. In this work, a
classification of these zeros in three types is introduced, based on the nature
of the components that interfere to produce them. Echoing noise-assisted
methods, a classification algorithm is proposed based on the addition of
independent noise realizations to build a 2D histogram describing the stability
of zeros. Features extracted from this histogram are later used to classify the
zeros using a non-supervised clusterization algorithm. A denoising approach
based on the classification of the spectrogram zeros is also introduced.
Examples of the classification of zeros are given for synthetic and real
signals, as well as a performance comparison of the proposed denoising
algorithm with another zero-based approach.
