Matching event sequences approach based on Weyl's discrepancy norm
|Titel||Matching event sequences approach based on Weyl's discrepancy norm|
|Buchtitel||Proceedings of the 1st IEEE International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP 2015)|
A novel approach for matching event sequences, that result from threshold-based sampling, is introduced. This approach relies on Hermann Weyl’s discrepancy norm, which plays a central role in the context of stability analysis of thresholdbased sampling. This metric is based on a maximal principle that evaluates intervals of maximal partial sums. It is shown that minimal length intervals of maximal discrepancy can be exploited, in order to efficiently cluster spikes by means of approximating step functions. In contrast to ordinary spikes, these spike clusters can not only be shifted, deleted or inserted, but also stretched and shrinked, which allows more flexibility in the matching process. A dynamic programming approach is applied in order to minimizing an energy functional of such deformation manipulations. Simulations based on integrate-andfire sampling show its potential above all regarding robustness.