Deconvolution of sparse spike trains accounting for wavelet phase shifts and colored noise
Frédéric Champagnat, Jérôme Idier, G. Demoment · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
The problem of the restoration of spiky sequences when the usual convolution model is corrupted by nonstationary wavelet phase-shifts is addressed. To this end, an extended convolution model driven by a Bernoulli-Gaussian (BG)-like process is introduced. This setting lends itself to easy extension of algorithms designed for BG deconvolution. A comparison of practical results obtained with this new method and BG deconvolution is provided. Numerical experiments indicate an increased robustness compared with standard BG methods.>