AbstractAn experimental study of laser ablation on the samples that comprise nanofilms of hafnium and zirconium dioxides on the surface of glass and silicon, and obtaining parameters of pulsed laser ablation in this work, provide new data describing the ablation mechanism. The samples were exposed to pulsed radiation from an Nd3+:YAG laser in order to measure the threshold energy density of laser ablation

AbstractMathematical simulations of invariant optical-digital correlator operation are performed with the LC SLM used for the input images display and for display of the correlation filter holograms. Different phase dependences on amplitude are considered, particularly the measured dependence of the LC SLM HoloEye LC 2002. A method for optimization of correlation filters to eliminate the object recognition

AbstractStructure of the fiber-optic recirculating loop memory with periodic 2R-regeneration of information flow in the optical range is designed. The modified optical fiber loop mirror for 2R-regeneration of wavelength division multiplexed return-to-zero signals is proposed. On the basis of the proposed mathematical model, using numerical modeling, the efficiency of the restoration of optical information

AbstractA method for visualization of volumetric defects in a ZnGeP2 single-crystal by digital holography method using strontium vapor laser radiation is proposed. The possibility of obtaining a volume distribution of defects with dimensions of ≥15–20 μm and their identification in a crystal is shown. The identification in a ZnGeP2 single-crystal of such volumetric defects as growth bands and needle

AbstractThe paper deals with the algorithms of optimal quantization and adaptive interpolation in interpolative and hierarchical compression of multidimensional signals. An uneven quantization scale optimization algorithm is invented to tackle the unknown number of quantization levels given soft requirements for the optimization criterion. An important instance of applying the quantizer to the compression

AbstractThis paper is concerned with the global Mittag-Leffler stability (GMLS) and global finite-time stability (GFTS) for fractional Hopfield neural networks (FHNNs) with Hölder neuron activation functions subject to nonlinear growth. Firstly, four functions possessing convexity are proposed, which can guarantee that four formulas with respect to the fractional derivative are established. Correspondingly

AbstractIn this paper, a parallel SSD (Single Shot MultiBox Detector) fusion network based on inverted residual structure (IR-PSN) is proposed to solve the problems of the lack of extracted feature information and the unsatisfactory effect of small object detection by deep learning. Firstly, the Inverted Residual Structure (IR) is adopted into the SSD network to replace the pooling layer. The improved

AbstractTraining Convolutional Neural Networks that do well in one-shot learning settings can have wide range of impacts on real-world datasets. In this paper, we explore an adversarial training method that learns a Siamese neural network in an end-to-end fashion for two models—ConvNets model that learns image embeddings from input image pair, and head model that further learns the distance between

AbstractIn this paper we discuss image processing algorithms for analysis of structures in the films of biological liquids obtained by the cuneiform dehydration method. In medical diagnostics the cuneiform dehydration may be considered as a promising method of biological liquids studies. Main types of structures in the biological liquid films are presented. Today the methods of interpretation and algorithms

AbstractThe problem of neural network synthesis on the precedents is addressed. The aim of the study is to create methods for radial-basis neural network model constructing having high levels of generalization and accuracy, which do not require user participation in the process of model building. The method of decision tree transforming into a neural network model is proposed. For a given sample, a

AbstractThe goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high-dimensional feature vectors are nowadays produced by convolutional neural networks. The methods to aggregate the features generated for each video frame are used to process the video sequences. A novel hierarchical recognition

AbstractAlthough Deep Neural Networks (DNNs) have performed great success in machine learning domain, they usually show poorly on few-shot learning tasks, where a classifier has to quickly generalize after getting very few samples from each class. A Model-Agnostic Meta Learning (MAML) model, which is able to solve new learning tasks, only using a small number of training data. A MAML model with a Convolutional

AbstractWith the rapid development of Internet technology, the data information on the network has also increased in an unprecedented amount. However, the emergence of this phenomenon makes it difficult for network users to find information of great value to themselves in the massive data. Therefore, score prediction is very important. It is an urgent task to establish an effective and practical scoring

AbstractIn social media, organizing friendship relationships is difficult since the more number of increasing users in Online Social Networks (OSN). To overcome this challenge, users in OSN heavily depend on grouping which is considered to be advantageous but at the same time found to be more cumbersome. More recently, recommender system and novel data clustering algorithm have been presented in OSN

AbstractIn the present paper, we present a multi-start method with dynamic cutting of “unpromising” starts of locally optimal algorithms for solving continuous unconditional optimization problems. We also describe our results of testing of the proposed method for solving problems of feed-forward neural network training.

AbstractAmong a number of problems in the behavior planning of an unmanned vehicle the central one is movement in difficult areas. In particular, such areas are intersections at which direct interaction with other road agents takes place. In our work, we offer a new approach to train of the intelligent agent that simulates the behavior of an unmanned vehicle, based on the integration of reinforcement

AbstractRadial Basis Function Neural Networks (RBFNNs) have been widely used for classification and function approximation tasks. So, it is worthy to try improving and developing new learning algorithms for RBFNNs in order to get better results. This paper presents a new learning method for RBFNNs. Hence, an improved learning algorithm for center adjustment of RBFNNs using Harmony search (HS) algorithm

AbstractPhysical structures changing their resistance in operation can serve as a basis for making elements of neural networks (synapses, neurons, etc.). The processes inducing changes of resistance are rather complicated and cannot be described readily. To demonstrate the potential of this sort of variable resistors it is possible to substitute a complex physical system by a simple mathematical model

AbstractData encryption is becoming increasingly relevant with the development of digital technologies. A particularly promising direction is the development of encryption methods based on optical transformations. Fractional Fourier Transform is a well-known method of encoding data, especially graphic. However, an assessment of the method’s resistance to unauthorized data decryption has not been carried

AbstractIn this paper, the global Mittag-Leffler stability of fractional Hopfield neural networks (FHNNs) with \(\delta \)-inverse hölder neuron activation functions are considered. By applying the Brouwer topological degree theory and inequality analysis techniques, the proof of the existence and uniqueness of equilibrium point is addressed. By constructing the Lure’s Postnikov-type Lyapunov functions

AbstractIn Free Space Optical Communication (FSO), the optical signal from the laser source severely affects while travelling through free space atmospheric channel due to scattering, absorption and other effects of atmospheric turbulence conditions. This degrades the performance of FSO communication. In this article, we have generated the hollow beam from the laser output by the inverse axicon lens

AbstractTo reduce random access memory (RAM) requirements and to increase speed of recognition algorithms we consider a weight discretization problem for trained neural networks. We show that an exponential discretization is preferable to a linear discretization since it allows one to achieve the same accuracy when the number of bits is 1 or 2 less. The quality of the neural network VGG-16 is already

AbstractThe problem of image understanding currently attracts considerable attention of researchers, since its solution is critically important for a significant number of applied problems. Among the most critical components of this problem is the semantic segmentation of images, which provides a classification of objects on the image at the pixel level. One of the applied problems in which semantic

AbstractWe research adaptive multidimensional signal interpolators based on switching between several interpolating functions at each signal sample. We perform the switching by decision rule, which is optimized for each signal in the parameter space of this decision rule. Algorithms for factorization and dimension reduction of decision rules are proposed. We investigate new classes of interpolating

AbstractArrival time of public vehicles to transport stops is a key point of information systems for passengers. Accurate information on the arrival time is important for travel arrangements since it helps to decrease the wait time at a stop and to choose an optimal alternate route. Recently, such information has been included to mobile navigation applications too. In the present paper, we analyze

AbstractIn the present paper we analyzed a change in the density of states of a two-dimensional Ising model when a next-next-neighbor interaction is introduced. In other words, we examined two-dimensional lattices with diagonal connections. The same as in a three-dimensional model in this case each spin has 6 connections. Since the model is planar, we can calculate the free energy and other characteristics

AbstractWe discuss the problem of mathematical and computer modeling of nonlinear controllable dynamical systems with incomplete knowledge about the object of modeling and the conditions of its operation. The suggested approach is based on a merging of theoretical knowledge for the system with training tools of artificial neural network (ANN) field. We present an extension of previously proposed semi-empirical

AbstractWe describe an oscillatory neural network designed as a system of generalized phase oscillators with a central element. It is shown that a winner-take-all principle can be realized in this system in terms of the competition of peripheral oscillators for the synchronization with a central oscillator. Several examples illustrate how this network can be used for the simulation of various cognitive

Abstract—This article presents the use of the Normalized Differences Vegetation Index (NDVI) time series based change detection method for agriculture phenology monitoring. NDVI make use of the multi-spectral remote sensing data band combinations techniques to find out landscape such as agriculture, vegetation, land use/cover, water bodies and forest. Geographic Information System (GIS) technology

AbstractThe models for estimating the contribution of the cross section geometry to the active medium gain of the He-Ne laser have been considered in this work. Expanding the range of studied cross sections it has been found that these models were not analytical and demand the approximate calculations. Modern methods and computing tools should clarify the results of 1960–1970 and it will bring to more

AbstractDuring the work, experimental studies of spongy bone tissue of animals after ovariectomy and evaluation of its regeneration by allogeneic hydroxyapatite (HAP) by Raman spectroscopy were carried out. Also deconvolution of Raman spectra of the studied samples was carried out. Coefficients allow to evaluate the efficiency of HAP for the correction of osteoresorption in modeling osteoporosis with

AbstractIn this work, we propose a novel model-based on a new Deep Hybrid Descriptor learning called DeepGLBSIF (Gabor Local Binarized Statistical Image Feature) for effective extraction and over-complete features in multilayer hierarchy. The typology of our methodology is the same as that of Convolutional Neural Network (CNN) which is one of the intensively-applied deep learning architectures. This

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AbstractAn overview of known works in active vision area and our recent results on application of the foveal visual preprocessor to detect the head motion parameters are presented. In overview, the main directions of research and development in the field of artificial foveal active vision have been considered. It is justified that: (i) for a successful solution of complex problems in this area and

AbstractThe effect of alternate polarization (alP) has been investigated for 400 × 200 Gbps super dense wavelength division multiplexing (SD-WDM) system using RAMAN-EDFA-RAMAN hybrid optical amplifier (HOA). Further evaluation has carried out for the characteristics of bit error rate (BER) and quality factor (Q-factor) for enhance long haul optical communication. Remarkable performances have recorded

AbstractThe paper concentrates on methods of fault protection of neural networks implemented as hardware operating in fixed-point mode. We have explored possible variants of error occurrence, as well as ways to eliminate them. For this purpose, networks of identical architecture based on VGG model have been studied. VGG SIMPLE neural network that has been chosen for experiments is a simplified version

AbstractA neural network approach has been developed for detecting EEG patterns accompanying the implementation of motor imagery, which are mental equivalents of real movements. The method is based on Local Approximation of Spectral Power using Radial Basis Functions (LASP-RBF) and the original algorithm for interpreting the time sequence of neural network responses. An asynchronous neural interface

AbstractFace detection and recognition plays an important role in many occasions. This study explored the application of convolutional neural network in face detection and recognition. Firstly, convolutional neural network was briefly analyzed, and then a face detection model including three convolution layers, four pooling layers, introduction layers and three fully connected layers was designed.

AbstractIn the present paper we discuss a problem of recognition of a state of agricultural vegetation using aerial data of different spatial resolutions. To solve this problem, we develop a classifier allowing us to divide the input images into three classes, which are “healthy vegetation”, “diseased vegetation”, and “soil”. The proposed classifier is based on two convolutional neural networks allowing

AbstractHybrid optical two-dimensional (2D) codes due to their large cardinality and improved system performance for constant weight have recently been designed and studied for optical CDMA system. In this manuscript, an attempt has been made to analyze the performance of four different 2D codes from a communication point of view; that describe their use to support a system under certain conditions

AbstractA diagonally connected two-dimensional lattice is the objective of the research. The model draws interest because each of its spins has 6 connects as in a 3D lattice. On the other hand, the planarity of the model allows us to use a strict polynomial algorithm to find its partition function and other characteristics. The Kasteleyn-Fisher algorithm is employed to carry out a computer simulation

AbstractIn this paper, the passivity and passification issue are considered for a class of dynamic memristor neural networks (DMNNs) with delays. Different from the models with respect to memristive neural networks in the literature, the flux-controlled dynamic memristors are used in the neurons and finite concentrated delays are accounted for in the interconnections. With the construction of suitable

AbstractThe reduction of the dimensionality of a parametric space is done in the adaptive interpolation of a multidimensional signal. A hybrid adaptive interpolator underlies the dimensionality reduction. The multidimensional hybrid interpolator uses structurally different algorithms to interpolate multidirectional sections of the signal. The approximation of some sections of the signal by other sections

AbstractIn this paper a framework of the heterogeneous system for an adaptive classification of multivariate numerical data is proposed. Considered data characterize the dynamics of the simulated responses of auditory nerve fibers as probability that represents the average of the ensemble for acoustic signals. The possibility to classify sound stimuli by means of analysis of the responses of the auditory

AbstractIn order to increase profits, foreign trade enterprises need to reduce costs. But cross-border RMB settlement can reduce costs of foreign trade enterprises, which avoids exchange rate risks to some extent and reduces losses. However, cross-border RMB settlement will still be affected by exchange rate changes. In order to explore the law of exchange rate changes and make predictions to reduce

AbstractAround one-third of the world’s population drinks water from groundwater resources. Of this, about 10 percent, approximately 300 million people, obtains water from groundwater resources. This study identify and mapping of groundwater potential zone for growing population, irrigation and industrial development, combining with remote sensing (RS), geographical information system (GIS) and field

AbstractMost of optical signals is collected using optical instruments. Although photodiodes have the same unilateral conductivity as ordinary diodes, it can act as a photoelectric sensor in circuit and play a significant role in signal acquisition. In this study, the photosensitivity of photodiode was studied, a circuit was designed selecting photodiode as photoelectric sensor, and the signal acquisition

AbstractThe dispersion of estimates of the time to achieve human level AI is discussed at length. Some of the reasons behind this diversity are exposed and thoroughly analyzed. A special role of human language in providing both natural human intelligence and AI is extensively discussed. The more straightforward and expectedly much faster than currently pursued way of proceeding to the goal is dotted

AbstractNew approaches of red blood cell (erythrocyte) controlling by the action of evanescent wave is proposed in the given research work. Theoretical and experimental models for describing the conditions of the erythrocyte transverse motion and the vertical spin realization have been analyzed in the special selected schemes. The use of a linearly polarized plane wave with azimuth of \( \pm \)45°

AbstractThe dynamic meta-anamorphosis method is considered as a promising tool for management decision support. The method helps activate eye-mindedness of a decision making person, simplify information examination and reduce decision latency. The paper describes the essence and algorithm of the method and gives examples of meta-anamorphoses. We consider the key approach to the calculation of the integral

AbstractLidar measurements of atmospheric gases in the spectral ranges 1.8–2.5 and 3–4 μm have been numerically simulated. The differential absorption lidar system based on optical parametric oscillators with nonlinear KTA and KTP crystals is described; it allows tuning laser radiation in the near/mid-IR wavelength regions. Lidar echoes have been experimentally recorded in the 1.8–2.5 and 3–4 μm wavelength

AbstractFor a 1D Ising model, we obtained an exact expression for the spectral density in an n-vicinity of the ground state and explained why our n-vicinity method with the Gaussian approximation of the spectral density did not applicable in this case. We also found an analytical expression for the distribution of magnetization at an arbitrary temperature. When the temperature tends to zero the distribution

AbstractThis article raises the question of neural networks application to control a boiler unit as a multidimensional system. The use of neural networks for managing technological processes helps to solve the problems of the operation of a complex control system, it improves its fail safety. The article proposes to apply a neural network to solve these problems. Technological process as a multidimensional

AbstractThe results of the study of synovial fluid (SF) of patients with knee joint osteoarthritis (OA). The optical analysis of the SF samples, harvested during exploratory punctures of knee joints of patients suffering the osteoarthrosis in different stages using the standard method, was made. A certain component composition of surface of SF samples that differs for healthy people and the patients

AbstractThis paper presents a Reversible Data Hiding method in grayscale digital images using Pixel Prediction Error. The prediction error of the prediction error is modified to store the secret data. The prediction of the image pixels is carried out using interpolation from neighboring pixels. The high spatial correlation of image pixels in natural images lead to prediction errors close to zero. In

AbstractThe paper considers the use of convolutional neural networks for the concurrent recognition of the gender and age of a person by video records of his face. The emphasis is on the incorporation of the approach into mobile video analytics systems. We have investigated the fusion of decisions obtained during the processing of each video frame, including the use of the classifier committee based

AbstractA mathematical model of visual system of the human observing images on optoelectronic device display is proposed. The model allows to formalize in linear approximation the physiological processes of registration and transformation of halftone object images in the human visual system in the presence of external and internal noise, and to estimate the detection probability of objects visual images

AbstractWe analyze adaptive algorithms for interpolation of multidimensional signals and propose interpolators based on auto-switching between simple interpolation functions in each point of a signal depending on local characteristics of the signal at this point. The switching is performed with the aid of a parametrized decision rule. To fined optimal values of the parameters of this decision rule

AbstractWith the development of internet, man-machine interaction has tended to be more important. Precise speech recognition has become an important means to achieve man-machine interaction. In this study, deep neural network model was used to enhance speech recognition performance. Feedforward fully connected deep neural network, time-delay neural network, convolutional neural network and feedforward

AbstractThis paper proposes a new framework for training radial basis function neural networks (RBFNN). Determination of the centers of the Gaussian functions in the hidden layer of RBF neural network highly affects the performance of the network. This paper presents a novel radial basis function using fuzzy C-means clustering algorithm based on Atanassov’s intuitionistic fuzzy set (A-IFS) theory.