SIMULATION CHAOTIC DYNAMICS OF RELATIVISTIC BACKWARD-WAVE OSCILLATOR WITH USING CHAOS THEORY AND QUANTUM NEURAL NETWORKS

Nonlinear simulation and forecasting chaotic evolutionary dynamics of such complex system as relativistic backward-wave oscillator is treated using the new combined method, based on chaos theory algorithms, concept geometric attractors, algorithms for quantum neural network simulation. It has been performed modelling multilayer photon echo case noisy input sequence. analysis, processing temporal dependence output amplitude oscillator, described by nonstationary nonlinear equations electromagnetic field motion a beam. The data Lyapunov’s exponents, Kolmogorov entropy, correlation coefficient between actual networks prognostic rows, referred to signal nonrelativistic (relativistic) are listed. combining advanced modern theory, compact attractors one effective or, in more general an model artificial intelligence etc, could provide very adequate quantitatively correct description most complicated systems, particular, ultrahigh-frequency electronics