AUTHOR=Bavandpour Mohammad , Soleimani Hamid , Linares-Barranco Bernabé , Abbott Derek , Chua Leon O. 

TITLE=Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications

JOURNAL=Frontiers in Neuroscience

VOLUME=9

YEAR=2015

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2015.00409

DOI=10.3389/fnins.2015.00409

ISSN=1662-453X

ABSTRACT=<p>This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4<italic>n</italic> memristors and no switch for implementing an <italic>n</italic>-cell system in comparison with 2<italic>n</italic><sup>2</sup> memristors and 2<italic>n</italic> switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.</p>