Communication systems based on chaotic synchronization are gaining interest in the area of secure and covert data transmission. In this paper, a novel digital communication technique based on a coherent chaotic data transmission approach is proposed. In general, this technique resembles the well-known approach based on the modulation of nonlinearity parameters. The key idea of this study is to modulate a signal by varying not the system parameter but the symmetry coefficient in discrete chaotic models obtained by the special numerical integration method. For this purpose, the self-adjoint semi-implicit integration method of order 2 is used to obtain discrete master and slave models of the considered chaotic oscillator. The experimental results explicitly show that, like during parameter modulation, transmitting and receiving oscillators may completely synchronize only if the symmetry coefficients are equal in both systems. The architecture of the communication system based on the proposed modulation is presented. The practical applicability of the approach is confirmed by transmitting a test binary sequence between the transmitter and receiver models and preliminary benchmarking of the obtained communication system. Since the symmetry coefficient modulation does not significantly impact the chaotic behavior of the transmitting digital system, its better suitability for covert messaging was experimentally confirmed by comparing it with the parameter modulation technique.

Chaos-based communications are a promising application of chaos theory and nonlinear dynamics. Their key features include concealed transmission, high security, and native broadband signals. Many studies have recently been published devoted to this technology. However, the practical implementations of chaos-based communications are rare due to multiple shortcomings: high hardware requirements, complex signal processing algorithms, and a lack of efficient modulation techniques for chaotic signals. In this study, we consider a simple hardware prototype of a coherent chaos-based communication system based on a novel type of modulation: adaptive symmetry of the finite-difference scheme used in a chaos generator. We explicitly demonstrate the possibility of covertly transmitting data using a chaotic transmitter and receiver implemented in a general-purpose microcontroller unit. A comparison between traditional parameter and symmetry modulation is given through a return map analysis and bit error rate estimation. The communication secrecy is analyzed using quantified return map analysis. The obtained results confirm the possibility of creating chaos-based communication systems based on symmetry modulation.

Josephson junctions (JJs) are superconductor-based devices used to build highly sensitive magnetic flux sensors called superconducting quantum interference devices (SQUIDs). These sensors may vary in design, being the radio frequency (RF) SQUID, direct current (DC) SQUID, and hybrid, such as D-SQUID. In addition, recently many of JJ’s applications were found in spiking models of neurons exhibiting nearly biological behavior. In this study, we propose and investigate a new circuit model of a sensory neuron based on DC SQUID as part of the circuit. The dependence of the dynamics of the designed model on the external magnetic flux is demonstrated. The design of the circuit and derivation of the corresponding differential equations that describe the dynamics of the system are given. Numerical simulation is used for experimental evaluation. The experimental results confirm the applicability and good performance of the proposed magnetic-flux-sensitive neuron concept: the considered device can encode the magnetic flux in the form of neuronal dynamics with the linear section. Furthermore, some complex behavior was discovered in the model, namely the intermittent chaotic spiking and plateau bursting. The proposed design can be efficiently applied to developing the interfaces between circuitry and spiking neural networks. However, it should be noted that the proposed neuron design shares the main limitation of all the superconductor-based technologies, i.e., the need for a cryogenic and shielding system.

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot.

One of the tasks in the development of chaos-based communication systems is choosing the synchronization parameters to achieve the minimum synchronization time. In this paper, we consider the possible solution to such an issue for synchronization of adaptive chaotic models. We propose a technique to determine adaptive symmetry and synchronization coefficients for the communication system based on the master/slave configuration. The presented approach involves estimating the synchronization time for various initial conditions and determining the optimal symmetry and synchronization coefficients using the average, minimum and maximum synchronizationtime for considered sets of values. The experimental results obtained for the Rössler system have shown that, in contrast to the synchronization coefficient, the symmetry coefficient does not significantly influence the synchronization time. Moreover, we discovered that thesynchronization of the adaptive models using the obtained parameters occurs faster than in previously proposed communication schemes based on the Rössler chaotic system. The described approach can be used to improve chaos-based communication schemes including embedded communication systems.

Maintaining ecosystems is one of the current leading public concerns. Some of the pressing problems that threaten water resources are pollution of water bodies with floating debris, illegal extraction of water resources, wear and tear of underwater communications. Therefore, the creation of special technical solutions is urgent. This paper reports a model-based design of an unmanned surface vehicle (USV), purposed to control and maintain the oxygen level and parameters such as acidity and the water temperature in rivers, lakes, inland waterways, and coastal waters. The developed USV navigation autopilot is described as a system with two inputs and one output. The autopilot selected is an adaptive controller based on the concept of proportional, integral, and derivative (PID). The autopilot is implemented on the STM32 microcontroller and allows precisely maintaining a given course, adjusting the speed and angle of rotation during wind drift and other influences. The new technique for sensor calibration and data acquisition is described. Simulation results are given, showing the performance of the autopilot algorithm in response to variations in the environment. The numerical experiments of the model have presented the result of confirming the sufficient correspondence between prototype characteristics and simulation results. Finally, thorough field trials were performed to verify the reliability and precision of the proposed solutions. The developed unmanned surface vehicle can be used for environmental monitoring (water sampling, hydrography, patrolling water areas). In turn, the solutions obtained will be suitable for the design of other USV of different sizes.