Skip to main content

Thin Film Electrochemical Memristive Systems for Bio-Inspired Computation

Buy Article:

$113.00 plus tax (Refund Policy)


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.


Document Type: Review Article


Publication date: March 1, 2011

More about this publication?
  • 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.
  • Editorial Board
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more