Increasing Neural-Based Pedestrian Detectors' Robustness to Adversarial Patch Attacks Using Anomaly Localization.

Object detection in images is a fundamental component of many safety-critical systems, such as autonomous driving, video surveillance systems, and robotics. Adversarial patch attacks, being easily implemented in the real world, provide effective counteraction to object detection by state-of-the-art neural-based detectors. It poses a serious danger in various fields of activity.

A contrast sensitivity model of the human visual system in modern conditions for presenting video content.

Digital video incurs many distortions during processing, compression, storage, and transmission, which can reduce perceived video quality. Developing adaptive video transmission methods that provide increased bandwidth and reduced storage space while preserving visual quality requires quality metrics that accurately describe how people perceive distortion. A severe problem for developing new video quality metrics is the limited data on how the early human visual system simultaneously processes spatial and temporal information.

Optimisation Challenge for a Superconducting Adiabatic Neural Network That Implements XOR and OR Boolean Functions.

In this article, we consider designs of simple analog artificial neural networks based on adiabatic Josephson cells with a sigmoid activation function. A new approach based on the gradient descent method is developed to adjust the circuit parameters, allowing efficient signal transmission between the network layers. The proposed solution is demonstrated on the example of a system that implements XOR and OR logical operations.

Strain-induced charge ordering above room temperature in rare-earth manganites.

Most known mixed manganites containing rare-earth elements demonstrate a pronounced charge ordering (CO) state below room temperature. The behavior of the magnetic susceptibility and electronic magnetic resonance of polycrystalline PrSrMnO/YSZ ( = 0.2 and = 0.

Multilayer Bolometric Structures for Efficient Wideband Communication Signal Reception.

It is known that the dielectric layer (resonator) located behind the conducting plate of the bolometer system can significantly increase its sensitivity near the resonance frequencies. In this paper, the possibility of receiving broadband electromagnetic signals in a multilayer bolometric meta-material made of alternating conducting (e.g.

The Impact of Impulsive Traffic on Cellular Internet of Things Network Performance Indicators.

The use of wireless sensor networks and the Internet of Things has increased dramatically in the last decade. The sensors measure the required parameters and send them to the data processing centers using one of the various wireless transmission technologies (often using cellular infrastructure) to make the appropriate decision. Files containing measurement information can arrive in bursts simultaneously, which is a critical issue to be aware of.

Theoretical Comparison of Different Envelope Elimination and Restoration Transmitter PWM Modulator Configurations to Expand the Possible Antenna Mismatch.

The main characteristics of high-efficiency switching-mode solid-state power amplifiers with envelope elimination and restoration (EER) methods depend on all their elements. In this article, we study the influence of the types and parameters of the envelope path low-pass filters (LPFs) on the EER transmitter out-of-band emissions. This article presents for the first time an analysis of EER transmitter operation where the output impedance of the PWM modulator is not equal to zero, as usual (with a one-sided loaded LPF), but is matched with the low-pass filter and the load (with a double-sided loaded LPF).

A bifunctional superconducting cell as flux qubit and neuron.

Josephson digital or analog ancillary circuits are an essential part of a large number of modern quantum processors. The natural candidate for the basis of tuning, coupling, and neromorphic co-processing elements for processors based on flux qubits is the adiabatic (reversible) superconducting logic cell. Using the simplest implementation of such a cell as an example, we have investigated the conditions under which it can optionally operate as an auxiliary qubit while maintaining its "classical" neural functionality.

Low-Pass Image Filtering to Achieve Adversarial Robustness.

In this paper, we continue the research cycle on the properties of convolutional neural network-based image recognition systems and ways to improve noise immunity and robustness. Currently, a popular research area related to artificial neural networks is adversarial attacks. The adversarial attacks on the image are not highly perceptible to the human eye, and they also drastically reduce the neural network's accuracy.

Investigation of FBMC-OQAM Equalization with Real Interference Prediction Algorithm Properties for MIMO Transmission Scheme.

Increasing the data transfer rate is an urgent task in cellular, high-frequency (HF) and special communication systems. The most common way to increase the data rate is to expand the bandwidth of the transmitted signal, which is often achieved through the use of multitone systems. One such system is the filter bank multicarrier (FBMC).

Hybrid Nanosystems of Antibiotics with Metal Nanoparticles-Novel Antibacterial Agents.

The appearance and increasing number of microorganisms resistant to the action of antibiotics is one of the global problems of the 21st century. Already, the duration of therapeutic treatment and mortality from infectious diseases caused by pathogenic microorganisms have increased significantly over the last few decades. Nanoscale inorganic materials (metals and metal oxides) with antimicrobial potential are a promising solution to this problem.

Peculiarities of Resonant Absorption of Electromagnetic Signals in Multilayer Bolometric Sensors.

We examine the effect of resonant absorption of electromagnetic signals in a silicon semiconductor plasma layer when the dielectric plate is placed behind it both experimentally and numerically. It is shown that such plate acts as a dielectric resonator and can significantly increase the electromagnetic energy absorption in the semiconductor for certain frequencies determined by the dielectric plate parameters. Numerical modelling of the effect is performed under the conditions of conducted experiment.

Broadband and Efficient Envelope Amplifier for Envelope Elimination and Restoration/Envelope Tracking Higher-Efficiency Power Amplifiers.

Increasing the efficiency of transmitters, as the largest consumers of energy, is relevant for any wireless communication devices. For higher efficiency, a number of methods are used, including envelope tracking and envelope elimination and restoration. Increasing the bandwidth of used frequencies requires expanding envelope modulators bandwidth up to 250-500 MHz or more.

Bifurcation Oscillator as an Advanced Sensor for Quantum State Control.

We study bifurcation behavior of a high-quality (high-Q) Josephson oscillator coupled to a superconducting qubit. It is shown that the probability of capture into the state of dynamic equilibrium is sensitive to qubit states. On this basis we present a new measurement method for the superposition state of a qubit due to its influence on transition probabilities between oscillator levels located in the energy region near the classical separatrix.

A superconducting adiabatic neuron in a quantum regime.

We explore the dynamics of an adiabatic neural cell of a perceptron artificial neural network in a quantum regime. This mode of cell operation is assumed for a hybrid system of a classical neural network whose configuration is dynamically adjusted by a quantum co-processor. Analytical and numerical studies take into account non-adiabatic processes as well as dissipation, which leads to smoothing of quantum coherent oscillations.

On the Problem of Restoring and Classifying a 3D Object in Creating a Simulator of a Realistic Urban Environment.

Since the 20th century, a rapid process of motorization has begun. The main goal of researchers, engineers and technology companies is to increase the safety and optimality of the movement of vehicles, as well as to reduce the environmental damage caused by the automotive industry. The difficulty of managing traffic flows is that cars are driven by a person and their behavior, even in similar situations, is different and difficult to predict.

End-to-End Train Horn Detection for Railway Transit Safety.

The train horn sound is an active audible warning signal used for warning commuters and railway employees of the oncoming train(s), assuring a smooth operation and traffic safety, especially at barrier-free crossings. This work studies deep learning-based approaches to develop a system providing the early detection of train arrival based on the recognition of train horn sounds from the traffic soundscape. A custom dataset of train horn sounds, car horn sounds, and traffic noises is developed to conduct experiments and analysis.

Uplink NOMA-MIMO Systems with Rayleigh Power Distribution.

The article is devoted to multiple-input multiple-output antenna systems, also called MIMO systems, which are widely used in wireless communication systems. In this article we consider a case when the MIMO system works in overloaded mode. In this mode MIMO systems can be considered as a system with non-orthogonal multiple access NOMA.

Tunable superconducting neurons for networks based on radial basis functions.

The hardware implementation of signal microprocessors based on superconducting technologies seems relevant for a number of niche tasks where performance and energy efficiency are critically important. In this paper, we consider the basic elements for superconducting neural networks on radial basis functions. We examine the static and dynamic activation functions of the proposed neuron.

Application of Approximation Constructions with a Small Number of Parameters for the Estimation of a Rayleigh Fading Multipath Channel with Doppler Spectrum Spreading.

In this article, an algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver is proposed. The received signal model uses approximations with a small number of parameters to reduce the computational complexity of the resulting algorithm. The estimation algorithm is obtained under the assumption of a priori uncertainty about the characteristics of the communication channel and noise distribution using the linear least squares method.

Computationally Efficient Implementation of Joint Detection and Parameters Estimation of Signals with Dispersive Distortions on a GPU.

The detector is an integral part of the device for receiving and processing radio signals. Signals that have passed through the ionospheric channel acquire an unknown Doppler shift and are subject to dispersion distortions. It is necessary to carry out joint detection and parameter estimation to improve reception quality and detection accuracy.

Equivalent MIMO Channel Matrix Sparsification for Enhancement of Sensor Capabilities.

One of the development directions of new-generation mobile communications is using multiple-input multiple-output (MIMO) channels with a large number of antennas. This requires the development and utilization of new approaches to signal detection in MIMO channels, since the difference in the energy efficiency and the complexity between the optimal maximum likelihood algorithm and simpler linear algorithms become very large. The goal of the presented study is the development of a method for transforming a MIMO channel into a model based on a sparse matrix with a limited number of non-zero elements in a row.

Noise Immunity and Robustness Study of Image Recognition Using a Convolutional Neural Network.

The problem surrounding convolutional neural network robustness and noise immunity is currently of great interest. In this paper, we propose a technique that involves robustness estimation and stability improvement. We also examined the noise immunity of convolutional neural networks and estimated the influence of uncertainty in the training and testing datasets on recognition probability.