Stoyan Kirilov

Analysis of the mutual inductive and capacitive connections and tolerances of memristors parameters of a memristor memory matrix

In this paper the mutual inductive and capacitive connections and tolerances of memristor parameters of a memristor memory matrix are investigated. An equivalent circuit of three neighboring memristors of a memory matrix with complicated mutual capacitive and inductive connection is presented. Then the memristors own parasitic capacitance and inductance are described. The mutual capacitances between the platinum rims of the memory matrix are calculated. Two possible values of the coefficient of magnetic coupling between the memristors are used. A SIMULINK model of the circuit of three neighboring memristors is developed. The simulation is made at pulse mode with 3 GHz actuating voltages. The main result is that the parasitic parameters do not strongly affect the memristor voltage drops at frequencies up to 3 GHz. However the tolerances of the memristor parameters have stronger effect on the circuit characteristics. Finally, some concluding remarks associated with the magnetic and capacitive influence between the memristors and the leakage and parasitic resistances of a memristor memory matrix are given.

Analysis of a serial circuit with two memristors and voltage source at sine and impulse regime

In the present paper the structure and principle of action of Williamss memristor are described. There are presented its basic parameters and the basic physical dependencies are confirmed. The analysis described here considers linear drift model of Williamss memristor. A SIMULINK model of circuit with two memristors is build with obtained formulae and Kirchhoffs voltage law. The basic results by the simulations organized in MATLAB and SIMULINK environment are given in graphical form. These results are associated with distortions of plateaus of impulses at different ratios between resistances of “opened” and “closed” states of Williamss memristor - ROFF and RON. There are given also interpreting of results, which confirms that a memristor with high ratio r is better than a memristor with small value of r. In conclusion there are given basic deductions and perspectives for future applications of memristor circuits.

Syntheses of a PSPICE model of a titanium-dioxide memristor and Wien memristor generator

In this paper a PSPICE model of the equivalent circuit of the titanium-dioxide memristor is created based on its current-voltage relationship and using linear ionic drift model. By use of this computer model a Wien memristor generator is created. The oscillator circuit is analyzed and the basic relationships and time diagrams are given. The phase portrait of the system is also presented. The regulation of the output voltage magnitude and of the frequency is realized by changing the memristors states using external pulse voltage sources. In the end, some concluding remarks about the memristor Wien generator investigated are given.

ADVANCED MEMRISTOR MODEL WITH A MODIFIED BIOLEK WINDOW AND A VOLTAGE-DEPENDENT VARIABLE EXPONENT

The main idea of the present research is to propose a new nonlinear ionic drift memristor model suitable for computer simulations of memristor elements for different voltages. For this purpose, a modified Biolek window function with a voltage-dependent exponent is applied. The proposed modified memristor model is based on Biolek model and due to this and to the use of a voltage-dependent positive integer exponent in the modified Biolek window function it has a new improved property changing the model nonlinearity extent dependent on the integer exponent in accordance with the memristor voltage. Several computer simulations were made for soft-switching and hard-switching modes and also for pseudo-sinusoidal alternating voltage with an exponentially increasing amplitude and the respective basic important time diagrams, state-flux and i-v relationships are established.

Synthesis and Analysis of a Memristor-Based Perceptron for Logical Function Emulation

The purpose of this research is to propose a new memristor-based synaptic device for use in perceptrons. A synaptic circuit made by two memristors is analyzed and a linear relationship between time and synaptic weight is obtained for rectangular input pulses. For adjusting the synaptic weight pulses with long duration and high magnitude are used. The operating input signals are with short duration and low amplitude to avoid altering the memristor state. A successful operation of the new memristor linear synapse is established after scaling the synaptic weight. Streszczenie. W pracy zaproponowano nowe urządzenie synaptyczne bazujące na memristorze, ktore mozna uzyc w perceptronach. Przeanalizowano obwod synaptyczny zbudowany z dwoch memristorow i dla prostokątnych impulsow wejściowych uzyskano liniowe zalezności pomiedzy czasem a wagą synaptyczną. W celu dopasowania wag synaptycznych uzyto impulsow o dlugim czasie trwania i duzej amplitudzie. Sygnaly wejściowe posiadają krotki czas trwania oraz malą amplitude w celu unikniecia zmiany stanu memristora. Po wyskalowaniu wagi synaptycznej uzyskano skuteczne dzialanie nowego memristora. (Synteza i analiza perceptronu opartego na memristorze dla emulacji funkcji logicznej)

Memristor Modeling In MATLAB & PSPICE.

The main purpose of the present investigation is to propose a new, modified Joglekar’s memristor model and to compare it with the Pickett model using several different window functions. The appropriate value of the exponent in the Joglekar’s window function is determined to approach the new model to the Pickett’s memristor model, which is based on practical experiments and measurements. The new memristor model is based on both Williams’, Joglekar’s and BCM models and it has their advantages considerations of the boundary conditions for hard-switching mode and ability for representation the nonlinear dopant drift. The memristor model proposed here is tunable and correctly expresses the behavior of the memristor element for lowand high-intensity electric fields, and is appropriate for computer simulations of different memristor nanostructures.