Maharadja: A System for the Real Time Simulation of RBF with the Mahalanobis Distance

作者:Bertrand Granado, Andréa Pinna, Luc Gaborit, Patrick Garda

摘要

This paper presents the architecture of Maharadja, a low-power consumption embedded system to perform the real time simulation of RBF networks with three possible distances: the Manhattan, the Euclidian or the Mahalanobis distance. This system achieves the same performances for the Manhattan distance, than existing RBF dedicated hardware, like Zisc or Ni1000. But it overtakes these systems because it can simulate Euclidian and Mahalanobis distances in real time. Moreover, Maharadja is designed for its integration into a ‘System On a Chip’.

论文关键词:FPGA, low-power consumption, Mahalanobis distance, neural hardware, RBF, real time

论文评审过程:

论文官网地址:https://doi.org/10.1023/A:1011309229584