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In this paper, we provide a novel approach to describe and analyze memristive circuits. This method is based on a Volterra series representation of the essential time functions of the circuit. This does not only provide the possibility of calculating voltages and currents over time in specific memristive networks, but describes the behavior of a general single memristor circuit, e.g. a circuit with...
A simple memristor-based oscillatory network has been recently proposed as building block for the realization of associative and dynamic oscillatory memories for spatio-temporal pattern recognition applications. The network was found to experience a gamut of complex dynamic behaviors. A complete picture of the network dynamics requires a preliminary study of the basic oscillator. Study of its local...
A method of analogue emulation of the memristor with its prescribed charge (qM) - flux (ϕM) constitutive relation is presented. The memristor is emulated via a resistor with nonlinear current (iR) - voltage (vR) relationship, and a mutator. The purpose of the mutator is to provide a similarity transformation of the current-voltage characteristic of the resistor into the constitutive relation of the...
Networks made up of bio-inspired neuron oscillatory circuits with nanoscale memristors may achieve the large connectivity and highly parallel processing power of biological systems. Memristor also has potential to reproduce the behavior of a biological synapse. As in a living creature the weight of a synapse is adapted by ionic flow through it, so the conductance of a memristor is controlled by flux...
An ideal memristor with single-valued odd-symmetric charge-flux nonlinearity is extensively proposed for chaos-based applications. However, according to our boundary condition-based memristor model, the nonlinearity of a memristor nano-structure is in general multi-valued with strong dependence on input and initial conditions. Nevertheless, provided the model is augmented with suitable boundary conditions,...
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