A new algorithm for iterative deconvolution of sparse spike trains
Yves Goussard, G. Demoment, Jérôme Idier · International Conference on Acoustics, Speech, and Signal Processing · 2002
An iterative algorithm for deconvolution of Bernoulli-Gaussian processes is presented. This detection-estimation problem is formulated as that of a change of initial conditions in linear least-squares estimation. An algorithm with a very simple structure is obtained. It allows the evaluation of either marginal or joint likelihood criteria without any approximation; the resulting method is easy to implement and computationally inexpensive and remains nearly optimal. >