This paper addresses the estimation of symmetric χ2-divergence between two point processes. We propose a novel approach by, first, mapping the space of spike trains in an appropriate functional space, and then, estimating the divergence in this functional space using a least square regression approach. We compare the proposed approach with other available methods on simulated data, and discuss its pros and cons.
|Title of host publication||Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on|
|Number of pages||4|
|Publication status||Published - 2011|