Deconvolution of sparse spike trains by iterated window maximization

@article{Kaaresen1997DeconvolutionOS,
  title={Deconvolution of sparse spike trains by iterated window maximization},
  author={Kjetil F. Kaaresen},
  journal={IEEE Trans. Signal Process.},
  year={1997},
  volume={45},
  pages={1173-1183}
}
  • Kjetil F. Kaaresen
  • Published in IEEE Trans. Signal Process. 1997
  • Computer Science, Mathematics
  • A new algorithm for deconvolution of sparse spike trains is presented. To maximize a joint MAP criterion, an initial configuration is iteratively improved through a number of small changes. Computational savings are achieved by precomputing and storing two correlation functions and by employing a window strategy. The resulting formulas are simple, intuitive, and efficient. In addition, they allow much more complicated transitions than state-space solutions such as Kormylo and Mendel's (1982… CONTINUE READING

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