Structural and Parametric Identification of Knowm Memristors

This paper proposes a novel identification method for memristive devices using Knowm memristors as an example. The suggested identification method is presented as a generalized process for a wide range of memristive elements. An experimental setup was created to obtain a set of intrinsic I–V curves for Knowm memristors. Using the acquired measurements data and proposed identification technique, we developed a new mathematical model that considers low-current effects and cycle-to-cycle variability. The process of parametric identification for the proposed model is described. The obtained memristor model represents the switching threshold as a function of the state variables vector, making it possible to account for snapforward or snapback effects, frequency properties, and switching variability. Several tools for the visual presentation of the identification results are considered, and some limitations of the proposed model are discussed.

Resonator method for measuring the polarizability of small components of composite materials

The creation of new composite materials with specified radio-frequency properties is often carried out using small-sized inclusions, while the polarizability parameters of these small bodies in electric and magnetic fields play a significant role. The paper considers the possibility of measuring the polarizability of small components of the composite in an open quasi-optical resonator. It is shown that the values of the electric and magnetic polarizability of small particles can be estimated from the shifts of the resonant frequencies that arise when a small scatterer is placed in the resonator.

Wavelet Based and Statistical EEG Analysis in Patients with Schizophrenia

Schizophrenia, which is considered a serious mental disorder and a psychological illness, is quite common in society today. Schizophrenia manifests itself with disordered thought development, hallucinations, and different behaviours and reactions. In this study, EEG data were collected and analyzed on a total of 84 subjects diagnosed with normal and schizophrenia. EEG data used as a diagnostic tool with low-resolution level has been used to distinguish between schizophrenic and normal individuals. First of all, statistical methods were used in the analyzes, and also frequency properties of the data were extracted by Wavelet analysis. As a result of the analysis, statistical findings include characteristics that distinguish between diagnosed schizophrenia and normal individuals. In addition, the findings obtained as a result of the Wavelet analysis were determined to distinguish between normal and schizophrenic individuals. While the mean used in statistical analysis takes the value 1.6 for normal individuals, it takes the value 2.9 for individuals diagnosed with schizophrenia. Also, in the results of Continuous Wavelet (CW) Analysis, very important findings were obtained in terms of detection in scale 16 and 64 bands.

POSSIBILITIES OF CYBER-PHYSICAL APPROACH TO STUDYING FREQUENCY PROPERTIES OF CLOSED SYSTEM WITH INCOMPLETE INFORMATION ABOUT CONTROL OBJECT MODEL

The article considers a method of reducing the time spent on the experimental study of the frequency properties of an object with an unknown mathematical model by using the cyber-physical approach to the automation of the experiment. Nonparametric estimates of unknown frequency characteristics of an object are received from experimental data on the reaction of the object's output to the input harmonic signal in the form of a mixture of sinusoidal signals of different frequencies. To divide the output signal into components corresponding to each frequency, a computer technology is used that implements an optimization procedure for finding the values of both real and imaginary frequency characteristics, according to the frequencies represented in the harmonic input signal. The method is also suitable for accelerated evaluation of the frequency characteristics of an object with an unknown delay. There are considered the aspects of frequency properties estimation in the problem of closed system stability analysis, which is supposed to control an object with incomplete information about its model using a series-connected proportional-integral controller. The results of quick estimating the frequency characteristics of the object are used to identify the parameters of its transfer function. To solve the parameterization problem, there are used automation tools for calculating the transfer function according to data on the points of frequency characteristics implemented as part of the open-access computer mathematics system Scilab. There is given an example illustrating the possibilities of developing a control system using a reduced-order object model, as one of the applications of the results of parametric identification of the transfer function

The use of the vulnerability factor in the study of vibration signals on the soil surface from the movement of subway electric trains

Microseismic vibrations of the upper part of the soil strata occur continuously under the influence of endogenous and exogenous processes of both natural and artificial origin. Micro-oscillations of technogenic nature are especially characteristic of densely built-up urban areas. The practice of monitoring seismological monitoring observations shows that under such conditions it is possible to observe various types of microseismic vibrations, including elastic vibration signals in the frequency range of 1—100 Hz, generated by passing subway trains. In the calculations of the seismic stability of the designed structures, special attention is paid to the resonance characteristics of the upper part of the soil strata, which at certain frequencies can significantly enhance seismic vibrations, for example, from external vibrations sources. By traditional methods, the characteristics of resonant oscillations and their accounting are carried out, as a rule, with an insufficient degree of reliability and completeness, as a result of whichand so they are usually used as auxiliary ones. In this paper, a methodological complex is considered using modern methods for measuring and processing microseismic signals in order to identify areas with maximum amplitudes of response to external elastic influences in the study area for construction and take them into account in the future in design and construction. The study of vibroseismic noises formed on the surface of the soil layer, for example, by passing subway trains, allows one to estimate the amplitude-frequency properties of these soils, and the spectral ratio of horizontal displacements of soils to vertical H/V and the derivative of these ratios — the coefficient of vulnerability of the Ky — provide a confident selection of weakened zones that are subject to the greatest impact of external elastic vibrations.

VIBRATONAL MECHANICS AND STOCHASTIC QUASI-RESONANCES

The concept of vibrational mechanics was pioneered in the works by Professor I.I. Blekhman and developed by his numerous disciples and coleagues. It is a powerful tool for the study of such systems with fast excitations, in which slow motion is of primary interest. One important application of this approach is the stochastic resonance, the phenomenon of resonance-like response of slow variables to intensity of stochastic excitation. This phenomenon is considered within the framework of vibrational mechanics as forced lowfrequency oscillations near the natural frequency, which evolves under the influence of changing high-frequency stochastic excitation. We propose a generalization of this approach to the case when the evolution of low-frequency properties of the system leads not to the equality of the natural frequency and the frequency of the external slow force, but to the loss of stability in a certain interval of the stochastic excitation intensity. Since in this case, as for stochastic resonance, the external manifestation of the process is the resonance-like response of the system, the considered effect can be called stochastic quasi-resonance, As an example, we consider a rotor with anisotropy of bending stiffness under the action of stochastic angular velocity oscillations.