  The analysis of the time-frequency content of a signal is a classical problem
in signal processing, with a broad number of applications in real life. Many
different approaches have been developed over the decades, which provide
alternative time-frequency representations of a signal each with its advantages
and limitations. In this work, following the success of nonlinear methods for
the decomposition of signals into intrinsic mode functions (IMFs), we first
provide more theoretical insights into the so-called Iterative Filtering
decomposition algorithm, proving an energy conservation result for the derived
decompositions. Furthermore, we present a new time-frequency representation
method based on the IMF decomposition of a signal, which is called IMFogram. We
prove theoretical results regarding this method, including its convergence to
the spectrogram representation for a certain class of signals, and we present a
few examples of applications, comparing results with some of the most well know
approaches available in the literature.
