Can One Design a Series of Brains for Neuromorphic Computing to solve complex inverse problems
Emerging Technologies
2019-03-07 v1
Abstract
In this position paper, we present a discussion on neuromorphic computing and especially the learning/training algorithm to design a series of brains with different memristive values to solve complex ill-posed inverse problems based on a Finite Element(FE) method. First, the neuromorphic computing is addressed and we focus on a type of memristive circuit computing that falls into the scope of neuromorphic computing. Secondly based on reference [1] in which the complex dynamics of the complex memristive circuit was studied, we design a method and an approach to train the memristive circuit so that the memristive values are optimally obtained.
Keywords
Cite
@article{arxiv.1903.02524,
title = {Can One Design a Series of Brains for Neuromorphic Computing to solve complex inverse problems},
author = {Mingyong Zhou},
journal= {arXiv preprint arXiv:1903.02524},
year = {2019}
}
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8 Pages