def estimStereoSIMMParams(self):
        self.computeStereoX()
        SXR = np.abs(self.XR) ** 2
        SXL = np.abs(self.XL) ** 2
        alphaR, alphaL, HGAMMA, HPHI, HF0, \
            betaR, betaL, HM, WM, recoError2 = SIMM.Stereo_SIMM(
            # the data to be fitted to:
            SXR, SXL,
            # the basis matrices for the spectral combs
            WF0=self.SIMMParams['WF0'],
            # and for the elementary filters:
            WGAMMA=self.SIMMParams['WGAMMA'],
            # number of desired filters, accompaniment spectra:
            numberOfFilters=self.SIMMParams['K'],
            numberOfAccompanimentSpectralShapes=self.SIMMParams['R'], 
            # if any, initial amplitude matrices for
            HGAMMA0=None, HPHI0=None,
            HF00=self.SIMMParams['HF00'],
            WM0=None, HM0=None,
            # Some more optional arguments, to control the "convergence"
            # of the algo
            numberOfIterations=self.SIMMParams['niter'],
            updateRulePower=1.0,
            stepNotes=self.SIMMParams['stepNotes'],
            lambdaHF0 = 0.0 / (1.0 * SXR.max()), alphaHF0=0.9,
            verbose=self.verbose, displayEvolution=False)