Title :
A new algorithm for iterative deconvolution of sparse spike trains
Author :
Goussard, Y. ; Demoment, G. ; Idier, J.
Author_Institution :
Ecole Superieure d´´Electricite, Gif-sur-Yvette, France
Abstract :
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
Keywords :
iterative methods; random processes; signal processing; Bernoulli-Gaussian processes; detection-estimation problem; initial conditions; iterative algorithm; iterative deconvolution; joint likelihood criteria; linear least-squares estimation; marginal criteria; signal processing; sparse spike trains; Acoustic distortion; Acoustic noise; Additive noise; Change detection algorithms; Deconvolution; Iterative algorithms; Linear systems; Reflectivity; Signal processing; Uninterruptible power systems;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.115707
