On using reservoir computing for sensing applications: exploring environment-sensitive memristor networks
Journal article, 2018

Recently, the SWEET sensing setup has been proposed as a way of exploiting reservoir computing for sensing. The setup features three components: an input signal (the drive), the environment and a reservoir, where the reservoir and the environment are treated as one dynamical system, a superreservoir. Due to the reservoir-environment interaction, the information about the environment is encoded in the state of the reservoir. This information can be inferred (decoded) by analysing the reservoir state. The decoding is done by using an external drive signal. This signal is optimised to achieve a separation in the space of the reservoir states: Under different environmental conditions, the reservoir should visit distinct regions of the configuration space. We examined this approach theoretically by using an environment-sensitive memristor as a reservoir, where the memristance is the state variable. The goal has been to identify a suitable drive that can achieve the phase space separation, which was formulated as an optimization problem, and solved by a genetic optimization algorithm developed in this study. For simplicity reasons, only two environmental conditions were considered (describing a static and a varying environment). A suitable drive signal has been identified based on intuitive analysis of the memristor dynamics, and by solving the optimization problem. Under both drives the memristance is driven to two different regions of the onedimensional state space under the influence of the two environmental conditions, which can be used to infer about the environment. The separation occurs if there is a synchronisation between the drive and the environmental signals. To quantify the magnitude of the separation, we introduced a quality of sensing index: The ability to sense depends critically on the synchronisation between the drive and environmental conditions. If this synchronisation is not maintained the quality of sensing deteriorates

memristor networks

sensing

environment-sensitive memristor

reservoir computing

Author

Vasileios Athanasiou

Chalmers, Microtechnology and Nanoscience (MC2), Electronics Material and Systems

Zoran Konkoli

Chalmers, Microtechnology and Nanoscience (MC2), Electronics Material and Systems

International Journal of Parallel, Emergent and Distributed Systems

1744-5760 (ISSN) 1744-5779 (eISSN)

Vol. 33 4 367-386

Areas of Advance

Information and Communication Technology

Nanoscience and Nanotechnology

Driving Forces

Sustainable development

Innovation and entrepreneurship

Subject Categories

Telecommunications

DOI

10.1080/17445760.2017.1287264

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Latest update

5/19/2020