Evolutionary spectrum estimation by positivity constrained deconvolution

We present a deconvolution technique to obtain the evolutionary spectrum (ES) of nonstationary signals by deconvolving the blurring effects of the time-frequency distribution (TFD) kernel from bilinear TFDs. The resulting spectrum is non-negative and has desirable properties such as higher resolution and higher concentration in time frequency. The new technique is computationally more efficient compared with the previously proposed entropy-based deconvolution technique, and, unlike the entropy method, it is not restricted to deconvolution of spectrograms with Gaussian windows. This makes the method applicable to deconvolving many of the bilinear time-frequency distributions.