Applied Physics A. 2013, 10.1007/s00339-013-7615-5.
Martin Ziegler, Karlheinz Ochs, Mirko Hansen, Hermann Kohlstedt.
Nanoelektronik, Technische Fakultat, Christian-Albrechts-Universität zu Kiel, 24143, Kiel, Germany and
Lehrstuhl für Digitale Kommunikationssysteme, Ruhr-Universität Bochum, 44780, Bochum, Germany
In nature, the capability of memorizing environmental changes and recalling past events can be observed in unicellular organisms like amoebas. Pershin and Di Ventra have shown that such learning behavior can be mimicked in a simple memristive circuit model consisting of an LC (inductance capacitance) contour and a memristive device. Here, we implement this model experimentally by using an Ag/TiO2−x /Al memristive device. A theoretical analysis of the circuit is used to gain insight into the functionality of this model and to give advice for the circuit implementation. In this respect, the transfer function, resonant frequency, and damping behavior for a varying resistance of the memristive device are discussed in detail.
Anticipation in biological systems is the process of speculation of the probable future based on the memory of past events. In nature, anticipation can be already observed in unicellular organisms like amoebas. In a biological experiment it has been shown that even such simple organisms can learn from time patterns, reflecting the environment adjacent to the unicellular organism. Their behavior may be described in terms of an inertial biological oscillator with a natural frequency. Varying environmental conditions differ from this frequency and generating a different (time) pattern. Amoebas can recognize the change in the pattern, memorize it, and predict future events so that amoebas can react even on partially presented pattern in the future. In a theoretical investigation Pershin and Di Ventra have shown that such anticipation behavior can be modeled in a simple memristive circuit model consisting of an LC contour and a memristive device. Memristive devices are two-terminal circuit elements which are able to remember the history of applied electrical potentials and feature a device characteristic that cannot be emulated by one of the other basic two-terminal circuit elements (resistance, inductance and capacitance). We implement the memristive model experimentally using an Ag/TiO2-x/Al memristive device. From a theoretical analysis of the electric circuit, important information about the transfer characteristic, resonant frequency, and damping behavior depending on the resistant state of the memristive device is obtained. Our analysis gives design conditions for the experimental implementation.
Ziegler, M; Ochs, K.; Hansen, M; Kohlstedt, H.: An electronic implementation of amoeba anticipation, Appl. Phys. A, DOI:10.1007/s00339-013-7615-5 (2013).