AUTHOR=Ieng Sio-Hoi , Lehtonen Eero , Benosman Ryad 

TITLE=Complexity Analysis of Iterative Basis Transformations Applied to Event-Based Signals

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 12 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2018.00373

DOI=10.3389/fnins.2018.00373

ISSN=1662-453X

ABSTRACT=This paper introduces an event-based methodology of 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 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.