  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.
