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Thin Film Electrochemical Memristive Systems for Bio-Inspired Computation

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Abstract:

We present the basic principles of the organization of organic memristor—the circuit element whose conductivity may vary according to its previous involvement in the current conduction. This property is an analog of the synaptic plasticity in biological systems, responsible for learning and memory. We describe also architecture and properties of adaptive networks based on the organic memristors. Finally, we discuss alternative strategies for the construction of statistical adaptive networks with element sizes in the nm range.

Keywords: ADAPTIVE NETWORKS; CONDUCTING POLYMERS; ORGANIC MEMRISTOR

Document Type: Review Article

DOI: http://dx.doi.org/10.1166/jctn.2011.1695

Publication date: March 1, 2011

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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