Two-tone spectroscopy of a SQUID metamaterial in the nonlinear regime

Compact microwave resonantors made of superconducting rings containing Josephson junctions (SQUIDs) are attractive candidates for building frequency tunable metamaterials with low losses and pronounced nonlinear properties. We explore the nonlinearity of a SQUID metamaterial by performing a two-tone resonant spectroscopy. The small-amplitude response of the metamaterial under strong driving by a microwave pump tone is investigated experimentally and theoretically. The transmission coefficient $S_{21}$ of a weak probe signal is measured in the presence of the pump tone. Increasing the power of the pump, we observe pronounced oscillations of the SQUID's resonance frequency $f_{\textrm{res}}$. The shape of these oscillations varies significantly with the frequency of the pump tone $f_{\textrm{dr}}$. The response to the probe signal displays instabilities and sidebands. A state with strong second harmonic generation is observed. We provide a theoretical analysis of these observations, which is in good agreement with the experimental results

Effects of acute and chronic hypohydration on tolerance to plus Gz acceleration in man. I - Physiological results

Effects of acute and chronic hypohydration on human physiological tolerance to gravity acceleratio

Evolution of Artificial Neural Networks

The history of artificial neural networks originates from the distant 1943, when Warren McCulloch and Walter Pitts formalized the notion of a neural network in a fundamental article on the logical calculation of ideas and nervous activity. This was the starting point in the history of artificial neural networks. Later, a huge number of different architectures of neural networks, learning methods and optimization algorithms were proposed. There was a time when neural networks were left in oblivion, but after the 1980s they were talked about again when John Hopfield introduced his famous full-mesh network. Today, artificial neural networks are indispensable tools in a huge number of tasks, such as tasks of forecasting and analyzing time series, the task of recognizing images and even emotions, classification tasks, natural language recognition, neural networks are used in industry, defense and medicine; many enumerate areas of their application. All this tells us that artificial neural networks have become part of modern life