A1 Journal article – refereed
Complexity Analysis of Iterative Basis Transformations Applied to Event-Based Signals

List of Authors: Ieng SH, Lehtonen E, Benosman R
Publication year: 2018
Journal name in source: FRONTIERS IN NEUROSCIENCE
Volume number: 12
ISSN: 1662-453X

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.

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Last updated on 2019-29-01 at 16:19