A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Complexity Analysis of Iterative Basis Transformations Applied to Event-Based Signals
Tekijät: Ieng SH, Lehtonen E, Benosman R
Kustantaja: FRONTIERS MEDIA SA
Julkaisuvuosi: 2018
Journal: Frontiers in Neuroscience
Tietokannassa oleva lehden nimi: FRONTIERS IN NEUROSCIENCE
Lehden akronyymi: FRONT NEUROSCI-SWITZ
Artikkelin numero: ARTN 373
Vuosikerta: 12
Sivujen määrä: 13
ISSN: 1662-453X
DOI: https://doi.org/10.3389/fnins.2018.00373
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/32123815
This paper introduces an event-based methodology to perform arbitrary linear basis transformations that encompass a broad range of practically important signal transforms, such as the discrete Fourier transform (DFT) and the discrete wavelet transform (DWT). We present a complexity analysis of the proposed method, and show that the amount of required multiply-and-accumulate operations is reduced in comparison to frame-based method in natural video sequences, when the required temporal resolution is high enough. Experimental results on natural video sequences acquired by the asynchronous time-based neuromorphic image sensor (ATIS) are provided to support the feasibility of the method, and to illustrate the gain in computation resources.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
